annotate generalized_linear.xml @ 9:717ab7f22435 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 4ed8c4f6ef9ece81797a398b17a99bbaf49a6978
author bgruening
date Wed, 30 May 2018 08:26:49 -0400
parents fd6c50f21cd0
children 44699d79d908
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1 <tool id="sklearn_generalized_linear" name="Generalized linear models" version="@VERSION@">
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2 <description>for classification and regression</description>
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3 <macros>
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4 <import>main_macros.xml</import>
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5 </macros>
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6 <expand macro="python_requirements"/>
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7 <expand macro="macro_stdio"/>
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8 <version_command>echo "@VERSION@"</version_command>
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9 <command><![CDATA[
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10 python "$glm_script" '$inputs'
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11 ]]>
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12 </command>
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13 <configfiles>
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14 <inputs name="inputs"/>
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15 <configfile name="glm_script">
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16 <![CDATA[
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17 import sys
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18 import json
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19 import numpy as np
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20 import sklearn.linear_model
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21 import pandas
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22 import pickle
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23 from scipy.io import mmread
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24
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25 @COLUMNS_FUNCTION@
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26
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27 input_json_path = sys.argv[1]
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28 params = json.load(open(input_json_path, "r"))
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29
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30 #if $selected_tasks.selected_task == "train":
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31
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32 algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"]
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33 options = params["selected_tasks"]["selected_algorithms"]["options"]
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34
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35 #if $selected_tasks.selected_algorithms.input_options.selected_input=="tabular":
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36 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header1"] else None
2
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37 X = read_columns(
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38 "$selected_tasks.selected_algorithms.input_options.infile1",
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39 "$selected_tasks.selected_algorithms.input_options.col1",
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40 sep='\t',
4
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41 header=header,
2
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42 parse_dates=True
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43 )
0
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44 #else:
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45 X = mmread(open("$selected_tasks.selected_algorithms.input_options.infile1", 'r'))
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46 #end if
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47
4
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48 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header2"] else None
2
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49 y = read_columns(
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50 "$selected_tasks.selected_algorithms.input_options.infile2",
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51 "$selected_tasks.selected_algorithms.input_options.col2",
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52 sep='\t',
4
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53 header=header,
2
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54 parse_dates=True
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55 )
0
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56
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57 my_class = getattr(sklearn.linear_model, algorithm)
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58 estimator = my_class(**options)
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59 estimator.fit(X,y)
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60 pickle.dump(estimator,open("$outfile_fit", 'w+'), pickle.HIGHEST_PROTOCOL)
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61
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62 #else:
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63 classifier_object = pickle.load(open("$selected_tasks.infile_model", 'r'))
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64 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
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65 prediction = classifier_object.predict(data)
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66 prediction_df = pandas.DataFrame(prediction)
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67 res = pandas.concat([data, prediction_df], axis=1)
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68 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None)
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69 #end if
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70
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71 ]]>
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72 </configfile>
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73 </configfiles>
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74 <inputs>
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75 <expand macro="sl_Conditional" model="zip">
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76 <param name="selected_algorithm" type="select" label="Select a linear model:">
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77 <option value="SGDClassifier" selected="true">Stochastic Gradient Descent (SGD) classifier</option>
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78 <option value="SGDRegressor">Stochastic Gradient Descent (SGD) regressor</option>
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79 <option value="LinearRegression">Linear Regression model</option>
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80 <option value="RidgeClassifier">Ridge classifier</option>
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81 <option value="Ridge">Ridge regressor</option>
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82 <option value="LogisticRegression">Logistic Regression</option>
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83 <option value="LogisticRegressionCV">Logitic Regression with Cross Validation</option>
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84 <option value="Perceptron">Perceptron</option>
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85 </param>
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86 <when value="SGDClassifier">
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87 <expand macro="sl_mixed_input"/>
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88 <section name="options" title="Advanced Options" expanded="False">
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89 <expand macro="loss">
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90 <option value="hinge" selected="true">hinge</option>
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91 <option value="log">log</option>
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92 <option value="modified_huber">modified huber</option>
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93 <option value="squared_hinge">squared hinge</option>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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94 <option value="perceptron">perceptron</option>
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diff changeset
95 </expand>
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parents:
diff changeset
96 <expand macro="penalty"/>
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parents:
diff changeset
97 <expand macro="alpha"/>
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diff changeset
98 <expand macro="l1_ratio"/>
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parents:
diff changeset
99 <expand macro="fit_intercept"/>
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parents:
diff changeset
100 <expand macro="n_iter" />
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
101 <expand macro="shuffle"/>
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diff changeset
102 <expand macro="epsilon"/>
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diff changeset
103 <expand macro="learning_rate_s" selected1="true"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
104 <expand macro="eta0"/>
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parents:
diff changeset
105 <expand macro="power_t"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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106 <!--class_weight-->
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diff changeset
107 <expand macro="warm_start" checked="false"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
108 <expand macro="random_state"/>
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diff changeset
109 <!--average-->
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110 </section>
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111 </when>
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112 <when value="SGDRegressor">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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113 <expand macro="sl_mixed_input"/>
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114 <section name="options" title="Advanced Options" expanded="False">
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115 <expand macro="loss" select="true"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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116 <expand macro="penalty"/>
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diff changeset
117 <expand macro="alpha"/>
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diff changeset
118 <expand macro="l1_ratio"/>
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diff changeset
119 <expand macro="fit_intercept"/>
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diff changeset
120 <expand macro="n_iter" />
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parents:
diff changeset
121 <expand macro="shuffle"/>
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parents:
diff changeset
122 <expand macro="epsilon"/>
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diff changeset
123 <expand macro="learning_rate_s" selected2="true"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
124 <expand macro="eta0" default_value="0.01"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
125 <expand macro="power_t" default_value="0.25"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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126 <expand macro="warm_start" checked="false"/>
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diff changeset
127 <expand macro="random_state"/>
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diff changeset
128 <!--average-->
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129 </section>
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130 </when>
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131 <when value="LinearRegression">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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132 <expand macro="sl_mixed_input"/>
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133 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
134 <expand macro="fit_intercept"/>
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diff changeset
135 <expand macro="normalize"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
136 <expand macro="copy_X"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
137 </section>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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138 </when>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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139 <when value="RidgeClassifier">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
140 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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141 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
142 <expand macro="ridge_params"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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143 </section>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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144 </when>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
145 <when value="Ridge">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
146 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
147 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
148 <expand macro="ridge_params"/>
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diff changeset
149 </section>
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150 </when>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
151 <when value="LogisticRegression">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
152 <expand macro="sl_mixed_input"/>
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diff changeset
153 <section name="options" title="Advanced Options" expanded="False">
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diff changeset
154 <expand macro="penalty"/>
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parents:
diff changeset
155 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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156 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
157 <expand macro="C"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
158 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
159 <expand macro="max_iter" default_value="100"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
160 <expand macro="warm_start" checked="false"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
161 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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162 <option value="liblinear" selected="true">liblinear</option>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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163 <option value="sag">sag</option>
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164 <option value="lbfgs">lbfgs</option>
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165 <option value="newton-cg">newton-cg</option>
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166 </param>
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diff changeset
167 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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168 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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169 <option value="ovr" selected="true">ovr</option>
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170 <option value="multinomial">multinomial</option>
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diff changeset
171 </param>
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172 <!--class_weight-->
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diff changeset
173 <expand macro="random_state"/>
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diff changeset
174 </section>
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175 </when>
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176 <when value="LogisticRegressionCV">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
177 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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178 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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179 <param argument="Cs" type="integer" value="10" label="Inverse of regularization strength" help="A grid of Cs values are chosen in a logarithmic scale between 1e-4 and 1e4. Like in support vector machines, smaller values specify stronger regularization. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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180 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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181 <param argument="cv" type="integer" optional="true" value="" label="Number of folds used in cross validation" help="If not set, the default cross-validation generator (Stratified K-Folds) is used. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
182 <expand macro="penalty"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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183 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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184 <expand macro="fit_intercept"/>
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185 <expand macro="max_iter" default_value="100"/>
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186 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
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187 <option value="liblinear" selected="true">liblinear</option>
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188 <option value="sag">sag</option>
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189 <option value="lbfgs">lbfgs</option>
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190 <option value="newton-cg">newton-cg</option>
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191 </param>
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192 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/>
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193 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
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194 <option value="ovr" selected="true">ovr</option>
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195 <option value="multinomial">multinomial</option>
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196 </param>
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197 <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Average scores across all folds" help=" "/>
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198 <expand macro="random_state"/>
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199 <!--scoring=None>
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200 <class_weight=None-->
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201 </section>
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202 </when>
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203 <when value="Perceptron">
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204 <expand macro="sl_mixed_input"/>
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205 <section name="options" title="Advanced Options" expanded="False">
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206 <expand macro="penalty" default_value="none"/>
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207 <expand macro="alpha"/>
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208 <expand macro="fit_intercept"/>
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209 <expand macro="n_iter" />
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210 <expand macro="shuffle"/>
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211 <expand macro="eta0" default_value="1"/>
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212 <expand macro="warm_start" checked="false"/>
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213 <expand macro="random_state" default_value="0"/>
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214 <!--class_weight=None-->
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215 </section>
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216 </when>
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217 </expand>
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218 </inputs>
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219 <outputs>
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220 <data format="tabular" name="outfile_predict">
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221 <filter>selected_tasks['selected_task'] == 'load'</filter>
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222 </data>
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223 <data format="zip" name="outfile_fit">
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224 <filter>selected_tasks['selected_task'] == 'train'</filter>
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225 </data>
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226 </outputs>
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227 <tests>
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228 <test>
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229 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
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230 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
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231 <param name="col1" value="1,2,3,4,5"/>
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232 <param name="col2" value="6"/>
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233 <param name="selected_task" value="train"/>
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234 <param name="selected_algorithm" value="SGDRegressor"/>
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235 <param name="random_state" value="10"/>
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236 <output name="outfile_fit" file="glm_model01" compare="sim_size" delta="500"/>
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237 </test>
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238 <test>
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239 <param name="infile_model" value="glm_model01" ftype="zip"/>
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240 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
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241 <param name="selected_task" value="load"/>
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242 <output name="outfile_predict" file="glm_result01" compare="sim_size" delta="500"/>
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243 </test>
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244 <test>
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245 <param name="infile1" value="train.tabular" ftype="tabular"/>
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246 <param name="infile2" value="train.tabular" ftype="tabular"/>
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247 <param name="col1" value="1,2,3,4"/>
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248 <param name="col2" value="5"/>
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249 <param name="selected_task" value="train"/>
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250 <param name="selected_algorithm" value="SGDClassifier"/>
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251 <param name="random_state" value="10"/>
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252 <output name="outfile_fit" file="glm_model02" compare="sim_size" delta="500"/>
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253 </test>
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254 <test>
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255 <param name="infile_model" value="glm_model02" ftype="zip"/>
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256 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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257 <param name="selected_task" value="load"/>
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258 <output name="outfile_predict" file="glm_result02"/>
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259 </test>
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260 <test>
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261 <param name="infile1" value="train.tabular" ftype="tabular"/>
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262 <param name="infile2" value="train.tabular" ftype="tabular"/>
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263 <param name="col1" value="1,2,3,4"/>
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264 <param name="col2" value="5"/>
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265 <param name="selected_task" value="train"/>
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266 <param name="selected_algorithm" value="RidgeClassifier"/>
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267 <param name="random_state" value="10"/>
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268 <output name="outfile_fit" file="glm_model03" compare="sim_size" delta="500"/>
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269 </test>
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270 <test>
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271 <param name="infile_model" value="glm_model03" ftype="zip"/>
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272 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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273 <param name="selected_task" value="load"/>
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274 <output name="outfile_predict" file="glm_result03"/>
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275 </test>
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276 <test>
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277 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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278 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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279 <param name="col1" value="1,2,3,4,5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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280 <param name="col2" value="6"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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281 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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282 <param name="selected_algorithm" value="LinearRegression"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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283 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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284 <output name="outfile_fit" file="glm_model04" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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285 </test>
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286 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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287 <param name="infile_model" value="glm_model04" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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288 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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289 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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290 <output name="outfile_predict" file="glm_result04" compare="sim_size"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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291 </test>
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292 <test>
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293 <param name="infile1" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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294 <param name="infile2" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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295 <param name="col1" value="1,2,3,4"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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296 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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297 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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298 <param name="selected_algorithm" value="LogisticRegression"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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299 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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300 <output name="outfile_fit" file="glm_model05" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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301 </test>
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302 <test>
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303 <param name="infile_model" value="glm_model05" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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304 <param name="infile_data" value="test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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305 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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306 <output name="outfile_predict" file="glm_result05"/>
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307 </test>
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308 <test>
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309 <param name="infile1" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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310 <param name="infile2" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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311 <param name="col1" value="1,2,3,4"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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312 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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313 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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314 <param name="selected_algorithm" value="LogisticRegressionCV"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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315 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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316 <output name="outfile_fit" file="glm_model06" compare="sim_size" delta="500"/>
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317 </test>
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318 <test>
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319 <param name="infile_model" value="glm_model06" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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320 <param name="infile_data" value="test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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321 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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322 <output name="outfile_predict" file="glm_result06"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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323 </test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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324 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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325 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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326 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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327 <param name="col1" value="1,2,3,4,5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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328 <param name="col2" value="6"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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329 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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330 <param name="selected_algorithm" value="Ridge"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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331 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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332 <output name="outfile_fit" file="glm_model07" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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333 </test>
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334 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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335 <param name="infile_model" value="glm_model07" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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336 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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337 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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338 <output name="outfile_predict" file="glm_result07" compare="sim_size"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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339 </test>
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340 <test>
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341 <param name="infile1" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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342 <param name="infile2" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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343 <param name="col1" value="1,2,3,4"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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344 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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345 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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346 <param name="selected_algorithm" value="LogisticRegressionCV"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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347 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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348 <output name="outfile_fit" file="glm_model08" compare="sim_size" delta="500"/>
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349 </test>
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350 <test>
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351 <param name="infile_model" value="glm_model08" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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352 <param name="infile_data" value="test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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353 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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354 <output name="outfile_predict" file="glm_result08"/>
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355 </test>
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356 </tests>
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357 <help><![CDATA[
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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358 ***What it does***
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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359 This module implements a set of linear models for classification and regression such as: SGD classification and regression, Linear and Ridge regression and classification. This wrapper is using sklearn.linear_model module at its core. For information about linear models and their parameter settings please refer to `Scikit-learn generalized linear models`_.
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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360
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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361 .. _`Scikit-learn generalized linear models`: http://scikit-learn.org/stable/modules/linear_model.html
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362
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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363 **1 - Methods**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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364 There are two groups of operations available:
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365
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366 1 - Train a model : A training set containing samples and their respective labels (or predicted values) are input. Based on the selected algorithm and options, an estimator object is fit to the data and is returned.
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367
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368 2 - Load a model and predict : An existing model predicts the class labels (or regression values) for a new dataset.
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369
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370 **2 - Trainig input**
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371 When you choose to train a model, you need a features dataset X and a labels set y. This tool expects tabular or sparse data for X and a single column for y (tabular). You can select a subset of columns in a tabular dataset as your features dataset or labels column. Below you find some examples:
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372
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373 **Sample tabular features dataset**
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374 The following training dataset contains 3 feature columns and a column containing class labels. You can simply select the first 3 columns as features and the last column as labels:
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375
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376 ::
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377
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378 4.01163365529 -6.10797684314 8.29829894763 1
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379 10.0788438916 1.59539821454 10.0684278289 0
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380 -5.17607775503 -0.878286135332 6.92941850665 2
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381 4.00975406235 -7.11847496542 9.3802423585 1
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382 4.61204065139 -5.71217537352 9.12509610964 1
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383
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384
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385 **Sample sparse features dataset**
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386 In this case you cannot specifiy a column range.
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387
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388 ::
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389
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390 4 1048577 8738
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391 1 271 0.020833
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392 1 1038 0.02461
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393 2 829017 0.016
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394 2 829437 0.012
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395 2 830752 0.025
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396 3 1047487 0.01
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397 3 1047980 0.02
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398 3 1048475 0.01
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399 4 608 0.016629
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400 4 1651 0.02519
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401 4 4053 0.04223
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402
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403
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404 **2 - Trainig output**
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405 The trained model is generated and output in the form of a binary file.
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406
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407
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408 **3 - Prediction input**
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409
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410 When you choose to load a model and do prediction, the tool expects an already trained estimator and a tabular dataset as input. The dataset contains new samples which you want to classify or predict regression values for.
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411
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412
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413 .. class:: warningmark
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414
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415 The number of feature columns must be the same in training and prediction datasets!
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416
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417
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418 **3 - Prediction output**
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419 The tool predicts the class labels for new samples and adds them as the last column to the prediction dataset. The new dataset then is output as a tabular file. The prediction output format should look like the training dataset.
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420
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421 ]]></help>
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422 <expand macro="sklearn_citation"/>
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423 </tool>