annotate PDAUG_ML_Models/PDAUG_ML_Models.py @ 12:03f954dd8360 draft default tip

"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit d396d7ff89705cc0dd626ed32c45a9f4029b1b05"
author jay
date Wed, 12 Jan 2022 19:42:36 +0000
parents c3f0b3a6339e
children
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1
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2 import numpy as np
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3 import sys,os
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4 from scipy import interp
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5 import pandas as pd
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6
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7 ###############################################################
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8 from sklearn.metrics import *
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9 from sklearn import preprocessing
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10 from sklearn.metrics import accuracy_score
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11 from sklearn.metrics import precision_recall_fscore_support
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12 from sklearn.metrics import roc_curve, auc
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13 from sklearn.model_selection import StratifiedKFold
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14 from sklearn.preprocessing import StandardScaler
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15 from sklearn.preprocessing import MinMaxScaler
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16 ###############################################################
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17 from sklearn.linear_model import LogisticRegression
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18 from sklearn.naive_bayes import GaussianNB
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19 from sklearn.neighbors import KNeighborsClassifier
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20 from sklearn.tree import DecisionTreeClassifier
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21 from sklearn.svm import SVC
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22 from sklearn.ensemble import RandomForestClassifier
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23 from sklearn.linear_model import SGDClassifier
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24 from sklearn.ensemble import GradientBoostingClassifier
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25 from sklearn.neural_network import MLPClassifier
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26 ###############################################################
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27 from itertools import cycle
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28 ################################################################
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29 from sklearn.model_selection import train_test_split
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33 def ReturnData(TrainFile, TestMethod, TestFile=None):
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34
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35 if (TestFile == None) and (TestMethod == 'Internal' or 'CrossVal'):
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36
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37 df = pd.read_csv(TrainFile, sep='\t')
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38 clm_list = df.columns.tolist()
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39 X_train = df[clm_list[0:len(clm_list)-1]].values
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40 y_train = df[clm_list[len(clm_list)-1]].values
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41 X_test = None
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42 y_test = None
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43 return X_train, y_train, X_test, y_test
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44
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45 elif (TestFile is not None) and (TestMethod == 'External'):
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46
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47 df = pd.read_csv(TrainFile, sep='\t')
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48 clm_list = df.columns.tolist()
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49 X_train = df[clm_list[0:len(clm_list)-1]].values
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50 y_train = df[clm_list[len(clm_list)-1]].values
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51 df1 = pd.read_csv(TestFile, sep='\t')
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52 clm_list = df1.columns.tolist()
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53 X_test = df1[clm_list[0:len(clm_list)-1]].values
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54 y_test = df1[clm_list[len(clm_list)-1]].values
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55 return X_train, y_train, X_test, y_test
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56
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57 elif (TestFile is not None) and (TestMethod == 'Predict'):
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58
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59 df = pd.read_csv(TrainFile, sep='\t')
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60 clm_list = df.columns.tolist()
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61 X_train = df[clm_list[0:len(clm_list)-1]].values
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62 y_train = df[clm_list[len(clm_list)-1]].values
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63
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64 df = pd.read_csv(TestFile, sep='\t')
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65 X_test = df
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66 y_test = None
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67 return X_train, y_train, X_train, y_train
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68
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69 def Fit_Model(TrainData, Test_Method, Algo, Selected_Sclaer, Workdirpath, htmlOutDir, OutFile, htmlFname, NoOfFolds=None, TestSize=None, TestData=None ):
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70
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71 if not os.path.exists(htmlOutDir):
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72 os.makedirs(htmlOutDir)
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73
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74 if Test_Method == 'Internal':
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75 X,y,_,_ = ReturnData(TrainData, Test_Method)
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76
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77 mean_tpr = 0.0
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78 mean_fpr = np.linspace(0, 1, 100)
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79
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80 specificity_list = []
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81 sensitivity_list = []
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82 precison_list = []
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83 mcc_list = []
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84 f1_list = []
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85
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86 folds = StratifiedKFold(n_splits=5)
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87 mean_tpr = 0.0
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88 mean_fpr = np.linspace(0, 1, 100)
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89
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90 ##########################
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91 accuracy_score_l = []
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92 cohen_kappa_score_l = []
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93 matthews_corrcoef_l = []
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94 precision_l = []
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95 recall_l = []
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96 f_score_l = []
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97 ##########################
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98
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99 folds = StratifiedKFold(n_splits=5)
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100
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101 for i, (train, test) in enumerate(folds.split(X, y)):
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102
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103 if Selected_Sclaer=='Min_Max':
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104 scaler = MinMaxScaler().fit(X[train])
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105 x_train = scaler.transform(X[train])
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106 x_test = scaler.transform(X[test])
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107
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108 elif Selected_Sclaer=='Standard_Scaler':
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109 scaler = preprocessing.StandardScaler().fit(X[train])
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110 x_train = scaler.transform(X[train])
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111 x_test = scaler.transform(X[test])
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112
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113 elif Selected_Sclaer == 'No_Scaler':
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114 x_train = X[train]
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115 x_test = X[test]
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116
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117 else:
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118 print('Scalling Method option was not correctly selected...!')
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119
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120 prob = Algo.fit(x_train, y[train]).predict_proba(x_test)
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121 predicted = Algo.fit(x_train, y[train]).predict(x_test)
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122
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123 fpr, tpr, thresholds = roc_curve(y[test], prob[:, 1])
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124 mean_tpr += interp(mean_fpr, fpr, tpr)
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125 mean_tpr[0] = 0.0
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126
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127 TN, FP, FN, TP = confusion_matrix(y[test], predicted).ravel()
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128
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129 accuracy_score_l.append(round(accuracy_score(y[test], predicted),3))
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130 a = precision_recall_fscore_support(y[test], predicted, average='macro')
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131 precision_l.append(round(a[0],3))
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132 recall_l.append(round(a[1],3))
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133 f_score_l .append(round(a[2],3))
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134
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135 accuracy_score_mean = round(float(sum(accuracy_score_l)/float(len(accuracy_score_l))),3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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136 precision_mean = round(float(sum(precision_l)/float(len(precision_l))),3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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137 recall_mean = round(float(sum(recall_l)/float(len(recall_l))),3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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138 f_score_mean = round(float(sum(f_score_l )/float(len(f_score_l ))),3)
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139
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140
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141 mean_tpr /= folds.get_n_splits(X, y)
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142 mean_tpr[-1] = 1.0
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143 mean_auc = auc(mean_fpr, mean_tpr)
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144
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145 ########################################################################################################################################
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146 V_header = ["Algo","accuracy","precision","recall","f1","mean_auc"] #
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147 v_values = [sys.argv[1], round(accuracy_score_mean, 3), round(precision_mean, 3), round(recall_mean, 3),round(f_score_mean, 3), round(mean_auc, 3)] #
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148 ########################################################################################################################################
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149
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150 df = pd.DataFrame([v_values], columns=V_header)
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151 df.to_csv(os.path.join(Workdirpath, OutFile), columns=V_header, sep='\t', index=None)
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152
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153 ############################################################
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154 from plotly.subplots import make_subplots
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155 import plotly.graph_objects as go
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156
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157 fig = make_subplots(
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158 rows=1, cols=2,
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159 specs=[[{"type": "xy"}, {"type": "scatter"}],], subplot_titles=("Algorithm performance", " ROC curve (AUC Score = %0.2f" % mean_auc+')'),
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160
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161 )
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162
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163 fig.add_trace( go.Bar(x=V_header[1:], y=v_values[1:],marker_color=['#F58518','#109618','#E45756','#1F77B4','#19D3F3']), row=1, col=1)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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164
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165 print (mean_fpr, mean_tpr)
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166
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167 fig.add_trace(go.Scatter(x=mean_fpr, y=mean_tpr), row=1, col=2)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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168 fig.update_yaxes(title_text="True Positive Rate", range=[0, 1], row=1, col=2)
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169 fig.update_xaxes(title_text="False Positive Rate", range=[0, 1], row=1, col=2)
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170 fig.update_yaxes(title_text="Score", range=[0, 1], row=1, col=1)
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171 fig.update_xaxes(title_text="Performance measures",row=1, col=1)
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172 fig.update_layout(height=700, showlegend=False, title="Machine ")
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173 fig.write_html(os.path.join(Workdirpath, htmlOutDir, htmlFname))
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174
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175 ############################################################
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176
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177 elif Test_Method == 'External':
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178
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179 X_train,y_train,X_test,y_test = ReturnData(TrainData, Test_Method, TestData)
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180
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181 if Selected_Sclaer=='Min_Max':
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182 scaler = MinMaxScaler().fit(X_train)
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183 x_train = scaler.transform(X_train)
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184 x_test = scaler.transform(X_test)
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185
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186 elif Selected_Sclaer=='Standard_Scaler':
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diff changeset
187 scaler = preprocessing.StandardScaler().fit(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
188 x_train = scaler.transform(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
189 x_test = scaler.transform(X_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
190
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
191 elif Selected_Sclaer == 'No_Scaler':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
192 x_train = X_train
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
193 x_test = X_test
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
194
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
195 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
196 print('Scalling Method option was not correctly selected...!')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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197
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
198 prob = Algo.fit(x_train, y_train).predict_proba(x_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
199 predicted = Algo.fit(x_train, y_train).predict(x_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
200
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
201 fpr, tpr, thresholds = roc_curve(y_test, prob[:, 1])
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
202 TN, FP, FN, TP = confusion_matrix(y_test, predicted).ravel()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
203 accu_score = accuracy_score(y_test, predicted)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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204
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
205 a = precision_recall_fscore_support(y_test, predicted, average='macro')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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206
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
207 pre_score = round(a[0],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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208 recall_score= round(a[1],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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209 f_score= round(a[2],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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210
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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211 pl.plot(fpr, tpr, '--', lw=2)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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212 auc_score = auc(fpr, tpr)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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213
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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214 a = precision_recall_fscore_support(y_test, predicted, average='macro')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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215 pre_score = round(a[0],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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216 rec_score = round(a[1],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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217 f_score = round(a[2],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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218
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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219 V_header = ["accuracy","presision","recall","f1","mean_auc"]
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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220 v_values = [accu_score, pre_score, rec_score, f_score, auc_score]
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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221
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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222 pl.figure()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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223 pl.plot(fpr, tpr, '-', color='red',label='AUC = %0.2f' % auc_score, lw=2)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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224 pl.xlim([0.0, 1.0])
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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225 pl.ylim([0.0, 1.05])
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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226 pl.xlabel('False Positive Rate')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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227 pl.ylabel('True Positive Rate')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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228 pl.title('ROC Cureve')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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229 pl.legend(loc="lower right")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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230
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
231 df = pd.DataFrame([v_values], columns=V_header)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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232 pl.savefig(os.path.join(Workdirpath, htmlOutDir, "out.png"))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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233 df.to_csv(os.path.join(Workdirpath, OutFile), columns=V_header, sep='\t')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
234 pl.figure()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
235 pl.bar(V_header, v_values, color=(0.2, 0.4, 0.6, 0.6))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
236 pl.xlabel('Accuracy Perameters', fontweight='bold', color = 'orange', fontsize='17', horizontalalignment='center')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
237 pl.savefig(os.path.join(Workdirpath, htmlOutDir, "2.png"))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
238 #pl.show()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
239 HTML_Gen(os.path.join(Workdirpath, htmlOutDir, htmlFname))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
240
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
241 elif Test_Method == "TestSplit":
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
242
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
243 X_train,y_train,_,_ = ReturnData(TrainData, Test_Method)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
244 X_train, X_test, y_train, y_test = train_test_split(X_train, y_train, test_size=float(TestSize), random_state=0)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
245
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
246
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
247 if Selected_Sclaer=='Min_Max':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
248 scaler = MinMaxScaler().fit(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
249 x_train = scaler.transform(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
250 x_test = scaler.transform(X_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
251
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
252 elif Selected_Sclaer=='Standard_Scaler':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
253 scaler = preprocessing.StandardScaler().fit(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
254 x_train = scaler.transform(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
255 x_test = scaler.transform(X_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
256
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
257 elif Selected_Sclaer == 'No_Scaler':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
258 x_train = X_train
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
259 x_test = X_test
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
260
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
261 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
262 print('Scalling Method option was not correctly selected...!')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
263
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
264 prob = Algo.fit(x_train, y_train).predict_proba(x_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
265 predicted = Algo.fit(x_train, y_train).predict(x_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
266 fpr, tpr, thresholds = roc_curve(y_test, prob[:, 1])
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
267 accu_score = accuracy_score(y_test, predicted)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
268
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
269 a = precision_recall_fscore_support(y_test, predicted, average='macro')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
270
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
271 pre_score = round(a[0],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
272 recall_score= round(a[1],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
273 f_score= round(a[2],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
274
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
275 pl.plot(fpr, tpr, '-', color='red',label='AUC = %0.2f' % accu_score, lw=2)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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276
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jay
parents:
diff changeset
277 pl.xlim([0.0, 1.0])
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
278 pl.ylim([0.0, 1.05])
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
279 pl.xlabel('False Positive Rate')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
280 pl.ylabel('True Positive Rate')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
281 pl.title('ROC Cureve')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
282 pl.legend(loc="lower right")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
283 pl.savefig(os.path.join(Workdirpath, htmlOutDir, "out.png"))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
284 pl.plot(fpr, tpr, '--', lw=2)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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285
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
286 auc_score = auc(fpr, tpr)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
287
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
288 a = precision_recall_fscore_support(y_test, predicted, average='macro')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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289 pre_score = round(a[0],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
290 rec_score = round(a[1],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
291 f_score = round(a[2],3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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292
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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293 V_header = ["accuracy","presision","recall","f1","mean_auc"]
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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294 v_values = [accu_score, pre_score, rec_score, f_score, auc_score]
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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295 df = pd.DataFrame([v_values], columns=V_header)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
296 df.to_csv(os.path.join(Workdirpath, OutFile), columns=V_header, sep='\t')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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297 pl.figure()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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298 pl.bar(V_header, v_values, color=(0.2, 0.4, 0.6, 0.6))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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299 pl.xlabel('Accuracy Perameters', fontweight='bold', color = 'orange', fontsize='17', horizontalalignment='center')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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300 pl.savefig(os.path.join(Workdirpath, htmlOutDir, "2.png"))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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301 #pl.show()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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302 HTML_Gen(os.path.join(Workdirpath, htmlOutDir, htmlFname))
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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303
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
304 elif Test_Method == "Predict":
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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305
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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306 X_train, y_train, X_test, _ = ReturnData(TrainData, Test_Method,TestData)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
307
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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308 if Selected_Sclaer=='Min_Max':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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309 scaler = MinMaxScaler().fit(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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310 x_train = scaler.transform(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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311 x_test = scaler.transform(X_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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312
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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313 elif Selected_Sclaer=='Standard_Scaler':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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314 scaler = preprocessing.StandardScaler().fit(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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315 x_train = scaler.transform(X_train)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
316 x_test = scaler.transform(X_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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317
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
318 elif Selected_Sclaer == 'No_Scaler':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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319 x_train = X_train
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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320 x_test = X_test
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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321
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
322 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
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323 print('Scalling Method option was not correctly selected...!')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
324
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
325 predicted = model.fit(x_train, y_train).predict(x_test)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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326
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
327
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
328 return predicted
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
329
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
330 def SVM_Classifier(C, kernel, degree, gamma, coef0, shrinking, probability, tol, cache_size, verbose, max_iter, decision_function_shape, randomState, breakties, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
331
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
332 if randomState == None:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
333 randomState =None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
334 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
335 randomState = int(randomState)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
336
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
337
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
338 if cache_size == None:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
339 cache_size =None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
340 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
341 cache_size = float(cache_size)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
342
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
diff changeset
343
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
344 if probability or shrinking == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
345 probability, shrinking = True, True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
346 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
347 probability, shrinking = False, False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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348
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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parents:
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349
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
350 if verbose == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
351 verbose = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
352 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
353 verbose = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
354
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
355
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
356 if breakties == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
357 breakties = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
358 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
359 breakties = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
360
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
361
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
362
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jay
parents:
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363
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
364 pera={
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
365
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
366 'C':float(C),
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
367 'kernel':kernel,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
368 'degree':int(degree), #3
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
369 'gamma':gamma, #default=scale
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
370 'coef0':float(coef0), #default=0.0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
371 'shrinking':shrinking, #P
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
372 'probability':probability,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
373 'tol':float(tol), #default=1e-3
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
374 'cache_size':cache_size,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
375 'verbose':verbose,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
376 'max_iter':int(max_iter),#default=-1
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
377 'decision_function_shape':decision_function_shape,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
378 'random_state':randomState,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
379 'break_ties':breakties
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
380 }
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
381
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
382
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
383 model = SVC(**pera )
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
384
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
385 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
386
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
387
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
388 def SGD_Classifier( loss, penalty, alpha, l1_ratio, fit_intercept, max_iter, tol, shuffle, verbose, epsilon, n_jobs, random_state, learning_rate, eta0, power_t, early_stopping, validation_fraction, n_iter_no_change, warm_start, average, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
389
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
390 if n_jobs == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
391 n_jobs =None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
392 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
393 n_jobs = int(n_jobs)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
394
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
395 if random_state == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
396 random_state =None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
397 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
398 random_state = int(random_state)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
399
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
400 if fit_intercept == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
401 fit_intercept = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
402 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
403 fit_intercept = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
404
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
405 if shuffle == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
406 shuffle = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
407 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
408 shuffle = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
409
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
410 if early_stopping == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
411 early_stopping = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
412 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
413 early_stopping = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
414
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
415 if warm_start == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
416 warm_start = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
417 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
418 warm_start = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
419
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
420 if average == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
421 average = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
422 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
423 average = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
424
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
425 pera = {"loss":loss,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
426 "penalty":penalty,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
427 "alpha":float(alpha),#0.0001
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
428 "l1_ratio":float(l1_ratio),#0.15
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
429 "fit_intercept":fit_intercept,#true
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
430 "max_iter":int(max_iter),#default=1000
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
431 "tol":float(tol),#default=1e-3
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
432 "shuffle":shuffle,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
433 "verbose":int(verbose), #default=0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
434 "epsilon":float(epsilon), #default=0.1
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
435 "n_jobs":n_jobs, #default=None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
436 "random_state":random_state, #default=None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
437 "learning_rate":learning_rate,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
438 "eta0":float(eta0), #default=0.0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
439 "power_t":float(power_t), #default=0.5
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
440 "early_stopping":early_stopping,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
441 "validation_fraction":float(validation_fraction), #default=0.1
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
442 "n_iter_no_change":int(n_iter_no_change), #default=5
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
443 "warm_start":warm_start,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
444 "average":average}
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
445
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
446 model = SGDClassifier(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
447
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
448 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
449
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
450
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
451 def DT_Classifier(criterion, splitter, max_depth, min_samples_split, min_samples_leaf, min_weight_fraction_leaf, random_state, max_leaf_nodes, min_impurity_decrease, min_impurity_split, presort, ccpalpha, max_features, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
452
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
453 if max_depth == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
454 max_depth =None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
455 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
456 max_depth = int(max_depth)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
457
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
458 if '.' in min_samples_split:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
459 min_samples_split = float(min_samples_split)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
460 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
461 min_samples_split = int(min_samples_split)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
462
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
463 if '.' in min_samples_leaf:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
464 min_samples_split = float(min_samples_leaf)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
465 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
466 min_samples_leaf = int(min_samples_leaf)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
467
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
468 if max_features == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
469 max_features = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
470 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
471 if '.' in max_features:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
472 max_features = float(max_features)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
473 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
474 max_features = int(max_features)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
475
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
476 if random_state == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
477 random_state = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
478 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
479 random_state = int(random_state)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
480
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
481
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
482 if max_leaf_nodes == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
483 max_leaf_nodes = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
484 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
485 max_leaf_nodes = int(max_leaf_nodes)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
486
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
487
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
488 pera = {"criterion":criterion,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
489 "splitter":splitter,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
490 "max_depth":max_depth,#int, default=None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
491 "min_samples_split":int(min_samples_split),#default=2
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
492 "min_samples_leaf":int(min_samples_leaf), #default=1
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
493 "min_weight_fraction_leaf":float(min_weight_fraction_leaf),#default=0.0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
494 "random_state":random_state, #default=None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
495 "max_leaf_nodes":max_leaf_nodes, #default=None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
496 "min_impurity_decrease":float(min_impurity_decrease),#float, default=0.0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
497 "min_impurity_split":float(min_impurity_split), #float, default=1e-7
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
498 "presort":presort,#default=deprecated
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
499 'ccp_alpha':float(ccpalpha),#non-negative float, default=0.0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
500 'max_features': max_features}#int, float or {"auto", "sqrt", "log2"}, default=None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
501
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
502 model = DecisionTreeClassifier(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
503
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
504 #Fit_Model('GBC.tsv', 'Internal', model, 'Min_Max', os.getcwd(), os.path.join(os.getcwd(),'report_dir'), 'out.tsv', 'out.html', NoOfFolds=3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
505 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
506
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
507
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
508 def GB_Classifier(loss, learning_rate, n_estimators, subsample, criterion, min_samples_split, min_samples_leaf, min_weight_fraction_leaf, max_depth, min_impurity_decrease,min_impurity_split, init, random_state, verbose, max_leaf_nodes, warm_start, presort, validation_fraction, n_iter_no_change, tol, ccpalpha, max_features, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
509
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
510 if '.' in min_samples_split:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
511 min_samples_split = float(min_samples_split)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
512 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
513 min_samples_split = int(min_samples_split)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
514
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
515 if '.' in min_samples_leaf:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
516 min_samples_split = float(min_samples_leaf)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
517 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
518 min_samples_leaf = int(min_samples_leaf)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
519
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
520 if max_features == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
521 max_features = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
522 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
523 if '.' in max_features:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
524 max_features = float(max_features)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
525 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
526 max_features = int(max_features)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
527
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
528 if random_state == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
529 random_state = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
530 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
531 random_state = int(random_state)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
532
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
533 if max_leaf_nodes == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
534 max_leaf_nodes = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
535 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
536 max_leaf_nodes = int(max_leaf_nodes)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
537
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
538 if warm_start == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
539 warm_start = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
540 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
541 warm_start = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
542
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
543
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
544 if n_iter_no_change == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
545 n_iter_no_change = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
546 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
547 n_iter_no_change = int(n_iter_no_change)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
548
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
549
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
550 if init == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
551 init = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
552 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
553 init = init
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
554
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
555
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
556 pera = {"loss":loss,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
557 "learning_rate":float(learning_rate),
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
558 "n_estimators":int(n_estimators), #int (default=100)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
559 "subsample":float(subsample), #float, optional (default=1.0)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
560 "criterion":criterion,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
561 "min_samples_split":min_samples_split, #int, float, optional (default=2)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
562 "min_samples_leaf":min_samples_leaf, #int, float, optional (default=1)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
563 "min_weight_fraction_leaf":float(min_weight_fraction_leaf), #float, optional (default=0.)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
564 "max_depth":int(max_depth), #integer, optional (default=3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
565 "min_impurity_decrease":float(min_impurity_decrease),#float, optional (default=0.)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
566 "min_impurity_split":float(min_impurity_split), #float, (default=1e-7)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
567 "init":init, #estimator or zero, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
568 "random_state":random_state, #int, RandomState instance or None, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
569 "verbose":int(verbose), #int, default: 0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
570 "max_features": max_features,#int, float, string or None, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
571 "max_leaf_nodes":max_leaf_nodes, #int or None, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
572 "warm_start":warm_start, #bool, default: False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
573 "presort":presort, #deprecated, default=deprecated
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
574 "validation_fraction":float(validation_fraction), #float, optional, default 0.1
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
575 "n_iter_no_change":n_iter_no_change, #int, default None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
576 "tol":float(tol),#default 1e-4
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
577 "ccp_alpha":float(ccpalpha)} #non-negative float, optional (default=0.0)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
578
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
579
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
580 model = GradientBoostingClassifier(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
581
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
582 #Fit_Model('GBC.tsv', 'Internal', model, 'Min_Max', os.getcwd(), os.path.join(os.getcwd(),'report_dir'), 'out.tsv', 'out.html', NoOfFolds=3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
583 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
584
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
585
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
586 def RF_Classifier( n_estimators, criterion, max_depth, min_samples_split, min_samples_leaf, min_weight_fraction_leaf, max_features, max_leaf_nodes, min_impurity_decrease, min_impurity_split, bootstrap, oob_score, n_jobs, random_state, verbose, warm_start, ccp_alpha, max_samples, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
587
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
588 if max_depth == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
589 max_depth = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
590 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
591 max_depth = int(max_depth)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
592
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
593 if '.' in min_samples_split:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
594 min_samples_split = float(min_samples_split)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
595 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
596 min_samples_split = int(min_samples_split)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
597
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
598 if '.' in min_samples_leaf:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
599 min_samples_split = float(min_samples_leaf)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
600 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
601 min_samples_leaf = int(min_samples_leaf)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
602
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
603 if max_features == 'auto':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
604 max_features = 'auto'
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
605 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
606 if '.' in max_features:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
607 max_features = float(max_features)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
608 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
609 max_features = int(max_features)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
610
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
611 if max_leaf_nodes == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
612 max_leaf_nodes = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
613 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
614 max_leaf_nodes = int(max_leaf_nodes)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
615
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
616 if bootstrap == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
617 bootstrap = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
618 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
619 bootstrap = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
620
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
621 if oob_score == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
622 oob_score = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
623 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
624 oob_score = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
625
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
626 if n_jobs == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
627 n_jobs = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
628 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
629 n_jobs = int(n_jobs)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
630
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
631 if random_state == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
632 random_state = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
633 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
634 random_state = int(random_state)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
635
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
636 if warm_start == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
637 warm_start = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
638 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
639 warm_start = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
640
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
641 if max_samples == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
642 max_samples = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
643 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
644 if '.' in max_samples:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
645 max_samples = float(max_samples)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
646 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
647 max_samples = int(max_samples)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
648
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
649
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
650 pera = {
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
651 "n_estimators":int(n_estimators), #integer, optional (default=100)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
652 "criterion":criterion, #string, optional (default='gini')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
653 "max_depth":max_depth, #integer #or None, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
654 "min_samples_split":min_samples_split,# int, float, optional (default=2)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
655 "min_samples_leaf":min_samples_leaf, #int, float, optional (default=1)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
656 "min_weight_fraction_leaf":float(min_weight_fraction_leaf),#float, optional (default=0.)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
657 "max_features":max_features, #int, float, string or None, optional (default='auto')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
658 "max_leaf_nodes":max_leaf_nodes, #int or None, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
659 "min_impurity_decrease":float(min_impurity_decrease), #float, optional (default=0.)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
660 "min_impurity_split":float(min_samples_split), #float, (default=1e-7)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
661 "bootstrap":bootstrap, #boolean, optional (default=True)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
662 "oob_score":oob_score, #bool (default=False)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
663 "n_jobs":n_jobs, #int or None, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
664 "random_state":random_state, #int, RandomState instance or None, optional (default=None)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
665 "verbose":int(verbose), #int, optional (default=0)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
666 "warm_start":warm_start,#bool, optional (default=False)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
667 "ccp_alpha":float(ccp_alpha),#non-negative float, optional (default=0.0)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
668 "max_samples": max_samples #int or float, default=None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
669 }
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
670
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
671 model = RandomForestClassifier(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
672 #Fit_Model('GBC.tsv', 'Internal', model, 'Min_Max', os.getcwd(), os.path.join(os.getcwd(),'report_dir'), 'out.tsv', 'out.html', NoOfFolds=3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
673 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
674
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
675
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
676 def LR_Classifier(penalty, dual, tol, C, fit_intercept, intercept_scaling, random_state, solver, max_iter, multi_class, verbose, warm_start, n_jobs, l1_ratio, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
677
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
678 if dual == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
679 dual = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
680 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
681 dual = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
682
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
683 if fit_intercept == "true":
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
684 fit_intercept = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
685 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
686 fit_intercept = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
687
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
688 if random_state == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
689 random_state = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
690 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
691 random_state = int(random_state)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
692
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
693 if warm_start == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
694 warm_start = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
695 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
696 warm_start = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
697
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
698 if n_jobs == "none":
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
699 n_jobs = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
700 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
701 n_jobs = int(n_jobs)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
702
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
703 if l1_ratio == "none":
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
704 l1_ratio = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
705 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
706 l1_ratio =float(l1_ratio)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
707
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
708 pera = {
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
709 "penalty":penalty, #l2
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
710 "dual":dual, #false
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
711 "tol":float(tol), #1e-4
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
712 "C":float(C), #1.0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
713 "fit_intercept":fit_intercept, #True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
714 "intercept_scaling":float(intercept_scaling), #1
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
715 "random_state":random_state, #None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
716 "solver":solver, #lbfgs
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
717 "max_iter":int(max_iter), #100
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
718 "multi_class":multi_class, #auto
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
719 "verbose":int(verbose), #0
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
720 "warm_start":warm_start,#False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
721 "n_jobs":n_jobs, #None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
722 "l1_ratio":l1_ratio} #None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
723
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
724 model = LogisticRegression(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
725
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
726 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
727
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
728
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
729 def KN_Classifier(n_neighbors, weights, algorithm, leaf_size, p, metric, metric_params, n_jobs, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
730
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
731 if n_jobs == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
732 n_jobs = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
733 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
734 n_jobs = int(n_jobs)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
735
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
736 pera = {
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
737 "n_neighbors":int(n_neighbors),#int5
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
738 "weights":weights,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
739 "algorithm":algorithm,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
740 "leaf_size":int(leaf_size), #int30
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
741 "p":int(p), #int2
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
742 "metric":metric, #minkowski
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
743 "n_jobs":n_jobs} #none
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
744
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
745 model = KNeighborsClassifier(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
746
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
747 #Fit_Model('GBC.tsv', 'Internal', model, 'Min_Max', os.getcwd(), os.path.join(os.getcwd(),'report_dir'), 'out.tsv', 'out.html', NoOfFolds=3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
748 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
749
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
750 def GNB_Classifier( var_smoothing, TrainFile, TestMethod, SelectedSclaer, NFolds, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
751
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
752 pera = {
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
753 "var_smoothing":float(var_smoothing)} #
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
754
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
755 model = GaussianNB(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
756
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
757 #Fit_Model('GBC.tsv', 'Internal', model, 'Min_Max', os.getcwd(), os.path.join(os.getcwd(),'report_dir'), 'out.tsv', 'out.html', NoOfFolds=3)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
758 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=int(NFolds), TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
759
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
760
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
761 def MLP_Classifier(hidden_layer_sizes, activation,solver,alpha,batch_size,learning_rate,learning_rate_init,power_t,max_iter,shuffle,random_state,tol,verbose,warm_start,momentum,nesterovs_momentum,early_stopping,validation_fraction,beta_1,beta_2,epsilon,n_iter_no_change,max_fun,TrainFile, TestMethod, SelectedSclaer, NFolds, Testspt, TestFile, OutFile, htmlOutDir, htmlFname, Workdirpath):
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
762
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
763 if shuffle == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
764 shuffle = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
765 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
766 shuffle = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
767
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
768 if nesterovs_momentum == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
769 nesterovs_momentum = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
770 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
771 nesterovs_momentum = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
772
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
773 if early_stopping == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
774 early_stopping = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
775 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
776 early_stopping = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
777
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
778 if random_state == 'none':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
779 random_state = None
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
780 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
781 random_state = int(random_state)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
782
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
783 if verbose == 'false':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
784 verbose = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
785 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
786 verbose = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
787
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
788 if warm_start == 'true':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
789 warm_start = True
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
790 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
791 warm_start = False
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
792
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
793 pera ={
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
794 'hidden_layer_sizes':hidden_layer_sizes, #=(100,),
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
795 'activation':activation, #='relu',
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
796 'solver':solver, #='adam',
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
797 'alpha':alpha, #=0.0001,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
798 'batch_size':batch_size, #='auto',
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
799 'learning_rate':learning_rate, #='constant',
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
800 'learning_rate_init':learning_rate_init, #=0.001,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
801 'power_t':power_t, #=0.5,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
802 'max_iter':max_iter, #=200,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
803 'shuffle':shuffle, #=True,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
804 'random_state':random_state, #=None,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
805 'tol':tol, #=0.0001,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
806 'verbose':verbose, #=False,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
807 'warm_start':warm_start, #=False,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
808 'momentum':momentum, #=0.9,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
809 'nesterovs_momentum':nesterovs_momentum, #=True,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
810 'early_stopping':early_stopping, #=False,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
811 'validation_fraction':validation_fraction, #=0.1,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
812 'beta_1':beta_1, #=0.9,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
813 'beta_2':beta_2, #=0.999,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
814 'epsilon':epsilon, #=1e-08,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
815 'n_iter_no_change':n_iter_no_change, #=10,
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
816 'max_fun':max_fun #=15000
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
817 }
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
818
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
819 model = MLPClassifier(**pera)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
820
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
821 Fit_Model(TrainData=TrainFile, Test_Method=TestMethod, Algo=model, Selected_Sclaer=SelectedSclaer, Workdirpath=Workdirpath, htmlOutDir=htmlOutDir, OutFile=OutFile, htmlFname=htmlFname, NoOfFolds=NFolds, TestSize=Testspt, TestData=TestFile)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
822
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
823
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
824 if __name__=="__main__":
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
825
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
826 import argparse
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
827
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
828 parser = argparse.ArgumentParser(description='Deployment tool')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
829 subparsers = parser.add_subparsers()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
830
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
831 svmc = subparsers.add_parser('SVMC')
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
832 svmc.add_argument("--C", required=False, default=1.0, help="Regularization parameter. The strength of the regularization is inversely proportional to C. Must be strictly positive. The penalty is a squared l2 penalty.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
833 svmc.add_argument("--kernel", required=False, default='rbf', help="Specifies the kernel type to be used in the algorithm. It must be one of 'linear', 'poly', 'rbf', 'sigmoid', 'precomputed' or a callable. If none is given, 'rbf' will be used. If a callable is given it is used to pre-compute the kernel matrix from data matrices; that matrix should be an array of shape (n_samples, n_samples).")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
834 svmc.add_argument("--degree", required=False, default=3, help="Degree of the polynomial kernel function ('poly'). Ignored by all other kernels.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
835 svmc.add_argument("--gamma", required=False, default='scale', help="Kernel coefficient for 'rbf', 'poly' and 'sigmoid'. if gamma='scale' (default) is passed then it uses 1 / (n_features * X.var()) as value of gamma, if 'auto', uses 1 / n_features.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
836 svmc.add_argument("--coef0", required=False, default=0.0, help="Independent term in kernel function. It is only significant in 'poly' and 'sigmoid'.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
837 svmc.add_argument("--shrinking", required=False, default=True, help="Whether to use the shrinking heuristic.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
838 svmc.add_argument("--probability", required=False, default=True, help="Whether to enable probability estimates. This must be enabled prior to calling fit, will slow down that method as it internally uses 5-fold cross-validation, and predict_proba may be inconsistent with predict")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
839 svmc.add_argument("--tol", required=False, default=0.001, help="Tolerance for stopping criterion.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
840 svmc.add_argument("--cache_size", required=False, default=200, help="Specify the size of the kernel cache (in MB).")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
841 svmc.add_argument("--verbose", required=False, default=False, help="Enable verbose output. Note that this setting takes advantage of a per-process runtime setting in libsvm that, if enabled, may not work properly in a multithreaded context.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
842 svmc.add_argument("--max_iter", required=False, default=-1, help="Hard limit on iterations within solver, or -1 for no limit.")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
jay
parents:
diff changeset
843 svmc.add_argument("--decision_function_shape", required=False, default='ovr', help="Whether to return a one-vs-rest ('ovr') decision function of shape (n_samples, n_classes) as all other classifiers, or the original one-vs-one ('ovo') decision function of libsvm which has shape (n_samples, n_classes * (n_classes - 1) / 2). However, one-vs-one ('ovo') is always used as multi-class strategy.")
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844 svmc.add_argument("--randomState", required=False, default=None, help="The seed of the pseudo random number generator used when shuffling the data for probability estimates. If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by np.random.")
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845 svmc.add_argument("--breakties", required=False, default=False, help="If true, decision_function_shape='ovr', and number of classes > 2, predict will break ties according to the confidence values of decision_function; otherwise the first class among the tied classes is returned. Please note that breaking ties comes at a relatively high computational cost compared to a simple predict." )
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846 svmc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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847 svmc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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848 svmc.add_argument("--SelectedSclaer", required=True, help="'Min_Max','Standard_Scaler','No_Scaler'")
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849 svmc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
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850 svmc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
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851 svmc.add_argument("--OutFile", required=False, default='Out.csv', help="Out.csv")
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852 svmc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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853 svmc.add_argument("--htmlFname", required=False, default='Out.html', help="HTML out file")
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854 svmc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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855
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856 sgdc = subparsers.add_parser('SGDC')
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857 sgdc.add_argument("--loss", required=False, default='log', help="The loss function to be used. Defaults to 'hinge', which gives a linear SVM. The possible options are 'hinge', 'log', 'modified_huber', 'squared_hinge', 'perceptron', or a regression loss: 'squared_loss', 'huber', 'epsilon_insensitive', or squared_epsilon_insensitive'.")
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858 sgdc.add_argument("--penalty", required=False, default='l2', help="The penalty (aka regularization term) to be used. Defaults to 'l2' which is the standard regularizer for linear SVM models. 'l1' and 'elasticnet' might bring sparsity to the model (feature selection) not achievable with 'l2'.")
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859 sgdc.add_argument("--alpha", required=False, default=0.0001, help="Constant that multiplies the regularization term. Defaults to 0.0001. Also used to compute learning_rate when set to 'optimal'.")
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860 sgdc.add_argument("--l1_ratio", required=False, default=0.15, help="The Elastic Net mixing parameter, with 0 <= l1_ratio <= 1. l1_ratio=0 corresponds to L2 penalty, l1_ratio=1 to L1. Defaults to 0.15.")
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861 sgdc.add_argument("--fit_intercept", required=False, default=True, help="Whether the intercept should be estimated or not. If False, the data is assumed to be already centered. Defaults to True.")
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862 sgdc.add_argument("--max_iter", required=False, default=1000, help="The maximum number of passes over the training data (aka epochs). It only impacts the behavior in the fit method, and not the partial_fit method.")
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863 sgdc.add_argument("--tol", required=False, default=0.001, help="The stopping criterion. If it is not None, the iterations will stop when (loss > best_loss - tol) for n_iter_no_change consecutive epochs.")
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864 sgdc.add_argument("--shuffle", required=False, default=True, help="Whether or not the training data should be shuffled after each epoch. Defaults to True.")
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865 sgdc.add_argument("--verbose", required=False, default=0, help="The verbosity level.")
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866 sgdc.add_argument("--epsilon", required=False, default=0.1, help="Epsilon in the epsilon-insensitive loss functions; only if loss is 'huber', 'epsilon_insensitive', or 'squared_epsilon_insensitive'. For 'huber', determines the threshold at which it becomes less important to get the prediction exactly right. For epsilon-insensitive, any differences between the current prediction and the correct label are ignored if they are less than this threshold.")
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867 sgdc.add_argument("--n_jobs", required=False, default='none', help="The number of CPUs to use to do the OVA (One Versus All, for multi-class problems) computation. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors. See Glossary for more details.")
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868 sgdc.add_argument("--random_state", required=False, default='none', help="The seed of the pseudo random number generator to use when shuffling the data. If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by np.random.")
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869 sgdc.add_argument("--learning_rate", required=False, default='optimal', help="The learning rate schedule:")
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870 sgdc.add_argument("--eta0", required=False, default=0.0, help="eta = eta0")
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871 sgdc.add_argument("--power_t", required=False, default=0.5, help="eta = 1.0 / (alpha * (t + t0)) where t0 is chosen by a heuristic proposed by Leon Bottou.")
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872 sgdc.add_argument("--early_stopping", required=False, default=False, help="MinMaxScaler")
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873 sgdc.add_argument("--validation_fraction", required=False, default=0.1, help="The proportion of training data to set aside as validation set for early stopping. Must be between 0 and 1. Only used if early_stopping is True.")
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874 sgdc.add_argument("--n_iter_no_change", required=False, default=5, help="Number of iterations with no improvement to wait before early stopping.")
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875 sgdc.add_argument("--warm_start", required=False, default=False, help="When set to True, reuse the solution of the previous call to fit as initialization, otherwise, just erase the previous solution.")
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876 sgdc.add_argument("--average", required=False, default=False, help="MinMaxScaler")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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877 sgdc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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878 sgdc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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879 sgdc.add_argument("--SelectedSclaer", required=True, help="'Min_Max','Standard_Scaler','No_Scaler'")
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880 sgdc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
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881 sgdc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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882 sgdc.add_argument("--OutFile", required=False, default='Out.csv', help="float, Max=1.0")
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883 sgdc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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884 sgdc.add_argument("--htmlFname", required=False, default='Out.html', help="")
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885 sgdc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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886
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887 dtc = subparsers.add_parser('DTC')
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888 dtc.add_argument("--criterion", required=False, default='gini', help="The function to measure the quality of a split. Supported criteria are 'gini' for the Gini impurity and 'entropy' for the information gain.")
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889 dtc.add_argument("--splitter", required=False, default='best', help="The strategy used to choose the split at each node. Supported strategies are 'best' to choose the best split and 'random' to choose the best random split." )
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890 dtc.add_argument("--max_depth", required=False, default='none', help="The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples.")
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891 dtc.add_argument("--min_samples_split", required=False, default='2', help="The minimum number of samples required to split an internal node: If int, then consider min_samples_split as the minimum number. If float, then min_samples_split is a fraction and ceil(min_samples_split * n_samples) are the minimum number of samples for each split.")
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892 dtc.add_argument("--min_samples_leaf", required=False, default='1', help="The minimum number of samples required to be at a leaf node. A split point at any depth will only be considered if it leaves at least min_samples_leaf training samples in each of the left and right branches. This may have the effect of smoothing the model, especially in regression.")
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893 dtc.add_argument("--min_weight_fraction_leaf", required=False, default=0.0, help="The minimum weighted fraction of the sum total of weights (of all the input samples) required to be at a leaf node. Samples have equal weight when sample_weight is not provided.")
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894 dtc.add_argument("--random_state", required=False, default='none', help="If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by np.random.")
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895 dtc.add_argument("--max_leaf_nodes", required=False, default='none', help="A node will be split if this split induces a decrease of the impurity greater than or equal to this value. The weighted impurity decrease equation is the following")
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896 dtc.add_argument("--min_impurity_decrease", required=False, default=0.0, help="")
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897 dtc.add_argument("--min_impurity_split", required=False, default=1e-09, help="Threshold for early stopping in tree growth. A node will split if its impurity is above the threshold, otherwise it is a leaf.")
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898 dtc.add_argument("--presort", required=False, default='deprecate', help="This parameter is deprecated and will be removed in v0.24.")
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899 dtc.add_argument("--ccpalpha", required=False, default=0.0, help="Complexity parameter used for Minimal Cost-Complexity Pruning. The subtree with the largest cost complexity that is smaller than ccp_alpha will be chosen. By default, no pruning is performed. See Minimal Cost-Complexity Pruning for details.")
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900 dtc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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901 dtc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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902 dtc.add_argument("--max_features", required=False, default='none')
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903 dtc.add_argument("--SelectedSclaer", required=True, help="'Min_Max',Standard_Scaler','No_Scaler'")
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904 dtc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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905 dtc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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906 dtc.add_argument("--OutFile", required=False, default='Out.csv', help="Out.tsv")
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907 dtc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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908 dtc.add_argument("--htmlFname", required=False, default='Out.html', help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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909 dtc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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910
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911 gbc = subparsers.add_parser('GBC')
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912 gbc.add_argument("--loss", required=False, default='deviance', help="loss function to be optimized. 'deviance' refers to deviance (= logistic regression) for classification with probabilistic outputs. For loss 'exponential' gradient boosting recovers the AdaBoost algorithm.")
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913 gbc.add_argument("--learning_rate", required=False, default=0.1, help="learning rate shrinks the contribution of each tree by learning_rate. There is a trade-off between learning_rate and n_estimators.")
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914 gbc.add_argument("--n_estimators", required=False, default=100, help="The number of boosting stages to perform. Gradient boosting is fairly robust to over-fitting so a large number usually results in better performance.")
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915 gbc.add_argument("--subsample", required=False, default=1.0, help="The fraction of samples to be used for fitting the individual base learners. If smaller than 1.0 this results in Stochastic Gradient Boosting. subsample interacts with the parameter n_estimators. Choosing subsample < 1.0 leads to a reduction of variance and an increase in bias.")
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916 gbc.add_argument("--criterion", required=False,default='friedman_mse', help="The function to measure the quality of a split. Supported criteria are 'friedman_mse' for the mean squared error with improvement score by Friedman, 'mse' for mean squared error, and 'mae' for the mean absolute error. The default value of 'friedman_mse' is generally the best as it can provide a better approximation in some cases.")
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917 gbc.add_argument("--min_samples_split", required=False, default='2', help="The minimum number of samples required to split an internal node: If int, then consider min_samples_split as the minimum number. If float, then min_samples_split is a fraction and ceil(min_samples_split * n_samples) are the minimum number of samples for each split.")
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918 gbc.add_argument("--min_samples_leaf", required=False, default='1', help="The minimum number of samples required to be at a leaf node. A split point at any depth will only be considered if it leaves at least min_samples_leaf training samples in each of the left and right branches. This may have the effect of smoothing the model, especially in regression.If int, then consider min_samples_leaf as the minimum number. If float, then min_samples_leaf is a fraction and ceil(min_samples_leaf * n_samples) are the minimum number of samples for each node.")
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919 gbc.add_argument("--min_weight_fraction_leaf", required=False, default=0, help="The minimum weighted fraction of the sum total of weights (of all the input samples) required to be at a leaf node. Samples have equal weight when sample_weight is not provided.")
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920 gbc.add_argument("--max_depth", required=False, default=3, help="maximum depth of the individual regression estimators. The maximum depth limits the number of nodes in the tree. Tune this parameter for best performance; the best value depends on the interaction of the input variables.")
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921 gbc.add_argument("--min_impurity_decrease", required=False, default=0.0, help="A node will be split if this split induces a decrease of the impurity greater than or equal to this value. The weighted impurity decrease equation is the following: 'N_t / N * (impurity - N_t_R / N_t * right_impurity - N_t_L / N_t * left_impurity'), where N is the total number of samples, N_t is the number of samples at the current node, N_t_L is the number of samples in the left child, and N_t_R is the number of samples in the right child. N, N_t, N_t_R and N_t_L all refer to the weighted sum, if sample_weight is passed. New in version 0.19.")
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922 gbc.add_argument("--min_impurity_split", required=False, default=0.00000007, help="Threshold for early stopping in tree growth. A node will split if its impurity is above the threshold, otherwise it is a leaf.")
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923 gbc.add_argument("--init", required=False,default='none', help="An estimator object that is used to compute the initial predictions. init has to provide fit and predict_proba. If 'zero', the initial raw predictions are set to zero. By default, a DummyEstimator predicting the classes priors is used.")
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924 gbc.add_argument("--random_state", required=False, default='none', help="If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by np.random.")
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925 gbc.add_argument("--max_features", required=False, default='none', help="The number of features to consider when looking for the best split: If int, then consider max_features features at each split. If float, then max_features is a fraction and int(max_features * n_features) features are considered at each split.If 'auto', then max_features=sqrt(n_features). If 'sqrt', then max_features=sqrt(n_features). If 'log2', then max_features=log2(n_features). If None, then max_features=n_features. Choosing max_features < n_features leads to a reduction of variance and an increase in bias. Note: the search for a split does not stop until at least one valid partition of the node samples is found, even if it requires to effectively inspect more than max_features features.")
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926 gbc.add_argument("--verbose",required=False, default=0, help="Enable verbose output. If 1 then it prints progress and performance once in a while (the more trees the lower the frequency). If greater than 1 then it prints progress and performance for every tree.")
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927 gbc.add_argument("--max_leaf_nodes", required=False, default=4, help="Grow trees with max_leaf_nodes in best-first fashion. Best nodes are defined as relative reduction in impurity. If None then unlimited number of leaf nodes.")
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928 gbc.add_argument("--warm_start", required=False, default='false', help="When set to True, reuse the solution of the previous call to fit and add more estimators to the ensemble, otherwise, just erase the previous solution." )
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929 gbc.add_argument("--presort", required=False,default='auto', help="This parameter is deprecated and will be removed in v0.24.")
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930 gbc.add_argument("--validation_fraction", required=False, default=0.1, help="The proportion of training data to set aside as validation set for early stopping. Must be between 0 and 1. Only used if n_iter_no_change is set to an integer.")
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931 gbc.add_argument("--n_iter_no_change", required=False, default=10, help="n_iter_no_change is used to decide if early stopping will be used to terminate training when validation score is not improving. By default it is set to None to disable early stopping. If set to a number, it will set aside validation_fraction size of the training data as validation and terminate training when validation score is not improving in all of the previous n_iter_no_change numbers of iterations. The split is stratified.")
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932 gbc.add_argument("--tol", required=False, default=0.0001, help="Tolerance for the early stopping. When the loss is not improving by at least tol for n_iter_no_change iterations (if set to a number), the training stops.")
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933 gbc.add_argument("--ccpalpha", required=False, default=0.0, help="Complexity parameter used for Minimal Cost-Complexity Pruning. The subtree with the largest cost complexity that is smaller than ccp_alpha will be chosen. By default, no pruning is performed. See Minimal Cost-Complexity Pruning for details.")
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934 gbc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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935 gbc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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936 gbc.add_argument("--SelectedSclaer", required=True, help="'Min_Max',Standard_Scaler','No_Scaler'")
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937 gbc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
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938 gbc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
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939 gbc.add_argument("--OutFile", required=False, default='Out.csv', help="Out.tsv")
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940 gbc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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941 gbc.add_argument("--htmlFname", required=False, default='Out.html', help="")
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942 gbc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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943
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944 rfc = subparsers.add_parser('RFC')
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945 rfc.add_argument("--n_estimators", required=False, default=100, help="The number of trees in the forest.")
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946 rfc.add_argument("--criterion", required=False, default='gini', help="The function to measure the quality of a split. Supported criteria are 'gini' for the Gini impurity and 'entropy' for the information gain. Note: this parameter is tree-specific." )
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947 rfc.add_argument("--max_depth", required=False, default='none', help="The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples.")
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948 rfc.add_argument("--min_samples_split", required=False, default='2', help="The minimum number of samples required to split an internal node: If int, then consider min_samples_split as the minimum number. If float, then min_samples_split is a fraction and ceil(min_samples_split * n_samples) are the minimum number of samples for each split.")
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949 rfc.add_argument("--min_samples_leaf", required=False, default='1', help="The minimum number of samples required to be at a leaf node. A split point at any depth will only be considered if it leaves at least min_samples_leaf training samples in each of the left and right branches. This may have the effect of smoothing the model, especially in regression.")
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950 rfc.add_argument("--min_weight_fraction_leaf", required=False, default=0.0, help="The minimum weighted fraction of the sum total of weights (of all the input samples) required to be at a leaf node. Samples have equal weight when sample_weight is not provided.")
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951 rfc.add_argument("--max_features", required=False, default='auto', help="The number of features to consider when looking for the best split:")
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952 rfc.add_argument("--max_leaf_nodes", required=False, default='none', help="Grow trees with max_leaf_nodes in best-first fashion. Best nodes are defined as relative reduction in impurity. If None then unlimited number of leaf nodes.")
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953 rfc.add_argument("--min_impurity_decrease", required=False, default=0.0, help="A node will be split if this split induces a decrease of the impurity greater than or equal to this value. The weighted impurity decrease equation is the following: N_t / N * (impurity - N_t_R / N_t * right_impurity - N_t_L / N_t * left_impurity) where N is the total number of samples, N_t is the number of samples at the current node, N_t_L is the number of samples in the left child, and N_t_R is the number of samples in the right child. N, N_t, N_t_R and N_t_L all refer to the weighted sum, if sample_weight is passed. New in version 0.19.")
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954 rfc.add_argument("--min_impurity_split", required=False, default=1e-7, help="Threshold for early stopping in tree growth. A node will split if its impurity is above the threshold, otherwise it is a leaf.")
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955 rfc.add_argument("--bootstrap", required=False, default='true', help="Whether bootstrap samples are used when building trees. If False, the whole datset is used to build each tree.")
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956 rfc.add_argument("--oob_score", required=False, default='false', help="Whether to use out-of-bag samples to estimate the generalization accuracy.")
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957 rfc.add_argument("--n_jobs", required=False, default=-1, help="The number of jobs to run in parallel. fit, predict, decision_path and apply are all parallelized over the trees. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors. See Glossary for more details." )
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958 rfc.add_argument("--random_state", required=False, default='none', help="Controls both the randomness of the bootstrapping of the samples used when building trees (if bootstrap=True) and the sampling of the features to consider when looking for the best split at each node (if max_features < n_features). See Glossary for details.")
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959 rfc.add_argument("--verbose", required=False, default=0, help="Controls the verbosity when fitting and predicting." )
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960 rfc.add_argument("--max_samples", required=False, default='none', help="")
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961 rfc.add_argument("--ccp_alpha", required=False, default=0.0, help="")
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962 rfc.add_argument("--warm_start", required=False, default='false', help="When set to True, reuse the solution of the previous call to fit and add more estimators to the ensemble, otherwise, just fit a whole new forest. See the Glossary.")
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963 rfc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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964 rfc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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965 rfc.add_argument("--SelectedSclaer", required=True, help="'Min_Max',Standard_Scaler','No_Scaler'")
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966 rfc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
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967 rfc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
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968 rfc.add_argument("--OutFile", required=False, default='Out.csv', help="Out.tsv")
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969 rfc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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970 rfc.add_argument("--htmlFname", required=False, default='Out.html', help="")
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971 rfc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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972
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973 lrc = subparsers.add_parser('LRC')
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974 lrc.add_argument("--penalty", required=False, default='l2', help="Used to specify the norm used in the penalization. The 'newton-cg', 'sag' and 'lbfgs' solvers support only l2 penalties. 'elasticnet' is only supported by the 'saga' solver. If 'none' (not supported by the liblinear solver), no regularization is applied." )
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975 lrc.add_argument("--dual", required=False, default='false', help="Dual or primal formulation. Dual formulation is only implemented for l2 penalty with liblinear solver. Prefer dual=False when n_samples > n_features.")
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976 lrc.add_argument("--tol", required=False, default=0.0001, help="Tolerance for stopping criteria.")
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977 lrc.add_argument("--C", required=False, default=1.0, help="Inverse of regularization strength; must be a positive float. Like in support vector machines, smaller values specify stronger regularization." )
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978 lrc.add_argument("--fit_intercept", required=False, default='true', help="Specifies if a constant (a.k.a. bias or intercept) should be added to the decision function." )
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979 lrc.add_argument("--intercept_scaling", required=False, default=1, help="Useful only when the solver 'liblinear' is used and self.fit_intercept is set to True. In this case, x becomes [x, self.intercept_scaling], i.e. a 'synthetic' feature with constant value equal to intercept_scaling is appended to the instance vector. The intercept becomes intercept_scaling * synthetic_feature_weight." )
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980 lrc.add_argument("--random_state", required=False, default=10, help="The seed of the pseudo random number generator to use when shuffling the data. If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by np.random. Used when solver == 'sag' or 'liblinear'.")
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981 lrc.add_argument("--solver", required=False, default='lbfgs', help="Algorithm to use in the optimization problem. For small datasets, 'liblinear' is a good choice, whereas 'sag' and 'saga' are faster for large ones. For multiclass problems, only 'newton-cg', 'sag', 'saga' and 'lbfgs' handle multinomial loss; 'liblinear' is limited to one-versus-rest schemes. 'newton-cg', 'lbfgs', 'sag' and 'saga' handle L2 or no penalty 'liblinear' and 'saga' also handle L1 penalty 'saga' also supports 'elasticnet' penalty 'liblinear' does not support setting penalty='none' Note that 'sag' and 'saga' fast convergence is only guaranteed on features with approximately the same scale. You can preprocess the data with a scaler from sklearn.preprocessing. New in version 0.17: Stochastic Average Gradient descent solver.")
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982 lrc.add_argument("--max_iter", required=False, default=100, help="Maximum number of iterations taken for the solvers to converge."),
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983 lrc.add_argument("--multi_class", required=False, default='auto', help="If the option chosen is 'ovr', then a binary problem is fit for each label. For 'multinomial' the loss minimised is the multinomial loss fit across the entire probability distribution, even when the data is binary. 'multinomial' is unavailable when solver='liblinear'. 'auto' selects 'ovr' if the data is binary, or if solver='liblinear', and otherwise selects 'multinomial'. New in version 0.18: Stochastic Average Gradient descent solver for 'multinomial' case.")
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984 lrc.add_argument("--verbose", required=False, default=0, help="For the liblinear and lbfgs solvers set verbose to any positive number for verbosity.")
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985 lrc.add_argument("--warm_start", required=False, default='false', help="When set to True, reuse the solution of the previous call to fit as initialization, otherwise, just erase the previous solution. Useless for liblinear solver. See the Glossary. New in version 0.17: warm_start to support lbfgs, newton-cg, sag, saga solvers.")
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986 lrc.add_argument("--n_jobs", required=False, default='none', help="Number of CPU cores used when parallelizing over classes if multi_class='ovr'. This parameter is ignored when the solver is set to 'liblinear' regardless of whether 'multi_class' is specified or not. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors. See Glossary for more details." )
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987 lrc.add_argument("--l1_ratio", required=False, default='none', help="The Elastic-Net mixing parameter, with 0 <= l1_ratio <= 1. Only used if penalty='elasticnet'. Setting 'l1_ratio=0 is equivalent to using penalty='l2', while setting l1_ratio=1 is equivalent to using penalty='l1'. For 0 < l1_ratio <1, the penalty is a combination of L1 and L2.")
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988 lrc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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989 lrc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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990 lrc.add_argument("--SelectedSclaer", required=True, help="'Min_Max',Standard_Scaler','No_Scaler'")
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991 lrc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
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992 lrc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
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993 lrc.add_argument("--OutFile", required=False, default='Out.csv', help="Out.tsv")
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994 lrc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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995 lrc.add_argument("--htmlFname", required=False, default='Out.html', help="")
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996 lrc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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997
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998 knc = subparsers.add_parser('KNC')
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999 knc.add_argument("--n_neighbors", required=False, default=5, help="Number of neighbors to use by default for kneighbors queries.")
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1000 knc.add_argument("--weights",required=False, default='uniform', help="weight function used in prediction. Possible values: 'uniform' : uniform weights. All points in each neighborhood are weighted equally. 'distance' : weight points by the inverse of their distance. in this case, closer neighbors of a query point will have a greater influence than neighbors which are further away. [callable] : a user-defined function which accepts an array of distances, and returns an array of the same shape containing the weights.")
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1001 knc.add_argument("--algorithm", required=False, default='auto', help="Algorithm used to compute the nearest neighbors:'ball_tree' will use BallTree 'kd_tree' will use KDTree 'brute' will use a brute-force search. 'auto' will attempt to decide the most appropriate algorithm based on the values passed to fit method. Note: fitting on sparse input will override the setting of this parameter, using brute force." )
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1002 knc.add_argument("--leaf_size", required=False, default=30, help="Leaf size passed to BallTree or KDTree. This can affect the speed of the construction and query, as well as the memory required to store the tree. The optimal value depends on the nature of the problem.")
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1003 knc.add_argument("--p", required=False, default=2, help="Power parameter for the Minkowski metric. When p = 1, this is equivalent to using manhattan_distance (l1), and euclidean_distance (l2) for p = 2. For arbitrary p, minkowski_distance (l_p) is used." )
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1004 knc.add_argument("--metric", required=False, default='minkowski', help="the distance metric to use for the tree. The default metric is minkowski, and with p=2 is equivalent to the standard Euclidean metric. See the documentation of the DistanceMetric class for a list of available metrics. If metric is 'precomputed', X is assumed to be a distance matrix and must be square during fit. X may be a Glossary, in which case only 'nonzero' elements may be considered neighbors.")
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1005 knc.add_argument("--metric_params", required=False, default=None, help="Additional keyword arguments for the metric function." )
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1006 knc.add_argument("--n_jobs", required=False, default='none', help="The number of parallel jobs to run for neighbors search. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors. See Glossary for more details. Doesn't affect fit method.")
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1007 knc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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1008 knc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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1009 knc.add_argument("--SelectedSclaer", required=True, help="'Min_Max',Standard_Scaler','No_Scaler'")
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1010 knc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
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1011 knc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
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1012 knc.add_argument("--OutFile", required=False, default='Out.csv', help="Out.tsv")
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1013 knc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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1014 knc.add_argument("--htmlFname", required=False, default='Out.html', help="")
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1015 knc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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1016
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1017 gnbc = subparsers.add_parser('GNBC')
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1018 #gnbc.add_argument("--priors", required=False, default=None, help="Prior probabilities of the classes. If specified the priors are not adjusted according to the data.")
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1019 gnbc.add_argument("--var_smoothing", required=False, default=1e-09, help="Portion of the largest variance of all features that is added to variances for calculation stability.")
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1020 gnbc.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
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1021 gnbc.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
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1022 gnbc.add_argument("--SelectedSclaer", required=True, help="'Min_Max',Standard_Scaler','No_Scaler'")
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1023 gnbc.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
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1024 gnbc.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
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1025 gnbc.add_argument("--OutFile", required=False, default='Out.csv', help="Out.tsv")
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1026 gnbc.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
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1027 gnbc.add_argument("--htmlFname", required=False, default='Out.html', help="")
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1028 gnbc.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
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1029
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1030 MLP = subparsers.add_parser('MLP')
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1031 MLP.add_argument("--hidden_layer_sizes", required=False, default=(100,), help="")
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1032 MLP.add_argument("--activation", required=False, default='relu', help="")
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1033 MLP.add_argument("--solver", required=False, default='adam', help="")
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1034 MLP.add_argument("--alpha", required=False, default=0.0001 , help="")
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1035 MLP.add_argument("--batch_size", required=False, default='auto', help="")
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1036 MLP.add_argument("--learning_rate", required=False, default='constant', help="")
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1037 MLP.add_argument("--learning_rate_init", required=False, default=0.001, help="")
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1038 MLP.add_argument("--power_t", required=False, default=0.5, help="")
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1039 MLP.add_argument("--max_iter", required=False, default=200, help="")
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1040 MLP.add_argument("--shuffle", required=False, default='true', help="")
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1041 MLP.add_argument("--random_state", required=False, default='none', help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1042 MLP.add_argument("--tol", required=False, default=0.0001, help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1043 MLP.add_argument("--verbose", required=False, default='false', help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1044 MLP.add_argument("--warm_start", required=False, default='false', help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1045 MLP.add_argument("--momentum", required=False, default=0.9, help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1046 MLP.add_argument("--nesterovs_momentum", required=False, default='true' ,help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1047 MLP.add_argument("--early_stopping", required=False, default='false' ,help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1048 MLP.add_argument("--validation_fraction", required=False, default=0.1 ,help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1049 MLP.add_argument("--beta_1", required=False, default=0.9, help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1050 MLP.add_argument("--beta_2", required=False , default=0.999, help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1051 MLP.add_argument("--epsilon", required=False, default=1e-08, help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1052 MLP.add_argument("--n_iter_no_change", required=False, default=10, help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1053 MLP.add_argument("--max_fun", required=False, default=15000, help="")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1054 MLP.add_argument("--TrainFile", required=True, default=None, help="Positive negative dataset Ex. 'Train.csv'")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1055 MLP.add_argument("--TestMethod", required=True, default=None, help="Internal','CrossVal', 'External', 'Predict'")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1056 MLP.add_argument("--SelectedSclaer", required=True, help="'Min_Max',Standard_Scaler','No_Scaler'")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1057 MLP.add_argument("--NFolds", required=False, default=5, help="int, Max=10")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1058 MLP.add_argument("--Testspt", required=False, default=0.2, help="float, Max=1.0")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1059 MLP.add_argument("--TestFile", required=False, default=None, help="Test data, 'Test.csv'")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1060 MLP.add_argument("--OutFile", required=False, default='Out.csv', help="Out.tsv")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1061 MLP.add_argument("--htmlOutDir", required=False, default=os.path.join(os.getcwd(),'report_dir'), help="HTML Out Dir")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1062 MLP.add_argument("--htmlFname", required=False, help="HTML out file", default="jai.html")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1063 MLP.add_argument("--Workdirpath", required=False, default=os.getcwd(), help="Working Directory Path")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1064
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1065 args = parser.parse_args()
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1066
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1067 if sys.argv[1] == 'SVMC':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1068 SVM_Classifier(args.C, args.kernel, args.degree, args.gamma, args.coef0, args.shrinking, args.probability, args.tol, args.cache_size, args.verbose, args.max_iter, args.decision_function_shape, args.randomState, args.breakties, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1069 elif sys.argv[1] == 'SGDC':
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diff changeset
1070 SGD_Classifier( args.loss, args.penalty, args.alpha, args.l1_ratio, args.fit_intercept, args.max_iter, args.tol, args.shuffle, args.verbose, args.epsilon, args.n_jobs, args.random_state, args.learning_rate, args.eta0, args.power_t, args.early_stopping, args.validation_fraction, args.n_iter_no_change, args.warm_start, args.average, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1071 elif sys.argv[1] == 'DTC':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1072 DT_Classifier(args.criterion, args.splitter, args.max_depth, args.min_samples_split, args.min_samples_leaf, args.min_weight_fraction_leaf, args.random_state, args.max_leaf_nodes, args.min_impurity_decrease, args.min_impurity_split, args.presort, args.ccpalpha, args.max_features, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1073 elif sys.argv[1] == 'GBC':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1074 GB_Classifier(args.loss, args.learning_rate, args.n_estimators, args.subsample, args.criterion, args.min_samples_split, args.min_samples_leaf, args.min_weight_fraction_leaf, args.max_depth, args.min_impurity_decrease, args.min_impurity_split, args.init, args.random_state, args.verbose, args.max_leaf_nodes, args.warm_start, args.presort, args.validation_fraction, args.n_iter_no_change, args.tol, args.ccpalpha, args.max_features, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1075 elif sys.argv[1] == 'RFC':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1076 RF_Classifier( args.n_estimators, args.criterion, args.max_depth, args.min_samples_split, args.min_samples_leaf, args.min_weight_fraction_leaf, args.max_features, args.max_leaf_nodes, args.min_impurity_decrease, args.min_impurity_split, args.bootstrap, args.oob_score, args.n_jobs, args.random_state, args.verbose, args.warm_start, args.ccp_alpha, args.max_samples, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1077 elif sys.argv[1] == 'LRC':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1078 LR_Classifier(args.penalty, args.dual, args.tol, args.C, args.fit_intercept, args.intercept_scaling, args.random_state, args.solver, args.max_iter, args.multi_class, args.verbose, args.warm_start, args.n_jobs, args.l1_ratio, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1079 elif sys.argv[1] == 'KNC':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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1080 KN_Classifier(args.n_neighbors, args.weights, args.algorithm, args.leaf_size, args.p, args.metric, args.metric_params, args.n_jobs, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
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diff changeset
1081 elif sys.argv[1] == 'GNBC':
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1082 GNB_Classifier( args.var_smoothing, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1083 elif sys.argv[1] == 'MLP' :
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diff changeset
1084 MLP_Classifier(args.hidden_layer_sizes, args.activation, args.solver, args.alpha, args.batch_size, args.learning_rate, args.learning_rate_init, args.power_t, args.max_iter, args.shuffle, args.random_state, args.tol, args.verbose, args.warm_start, args.momentum, args.nesterovs_momentum, args.early_stopping, args.validation_fraction, args.beta_1, args.beta_2, args.epsilon, args.n_iter_no_change, args.max_fun, args.TrainFile, args.TestMethod, args.SelectedSclaer, args.NFolds, args.Testspt, args.TestFile, args.OutFile, args.htmlOutDir, args.htmlFname, args.Workdirpath)
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1085 else:
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1086 print ("option not correct")
c3f0b3a6339e "planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit a9bd83f6a1afa6338cb6e4358b63ebff5bed155e"
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diff changeset
1087 exit()
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diff changeset
1088