Mercurial > repos > bgruening > sklearn_model_validation
annotate model_validation.xml @ 33:5d5d9cc554f9 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f031d8ddfb73cec24572648666ac44ee47f08aad
author | bgruening |
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date | Thu, 11 Aug 2022 08:49:05 +0000 |
parents | 4b359039f09f |
children | 1fe00785190d |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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1 <tool id="sklearn_model_validation" name="Model Validation" version="@VERSION@" profile="20.05"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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2 <description>includes cross_validate, cross_val_predict, learning_curve, and more</description> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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3 <macros> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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4 <import>main_macros.xml</import> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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5 </macros> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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6 <expand macro="python_requirements" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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7 <expand macro="macro_stdio" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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8 <version_command>echo "@VERSION@"</version_command> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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9 <command> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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10 <![CDATA[ |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ba6a47bdf76bbf4cb276206ac1a8cbf61332fd16"
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11 export HDF5_USE_FILE_LOCKING='FALSE'; |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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12 python "$sklearn_model_validation_script" '$inputs' |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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13 ]]> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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14 </command> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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15 <configfiles> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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16 <inputs name="inputs" /> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
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17 <configfile name="sklearn_model_validation_script"> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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18 <![CDATA[ |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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19 import imblearn |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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20 import joblib |
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333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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21 import json |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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22 import numpy as np |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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23 import os |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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24 import pandas as pd |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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25 import pickle |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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26 import pprint |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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27 import skrebate |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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28 import sys |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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29 import warnings |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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30 import xgboost |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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31 from mlxtend import classifier, regressor |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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32 from sklearn import ( |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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33 cluster, compose, decomposition, ensemble, feature_extraction, |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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34 feature_selection, gaussian_process, kernel_approximation, metrics, |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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35 model_selection, naive_bayes, neighbors, pipeline, preprocessing, |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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36 svm, linear_model, tree, discriminant_analysis) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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37 from sklearn.model_selection import _validation |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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38 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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39 from galaxy_ml.utils import (SafeEval, get_cv, get_scoring, load_model, |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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40 read_columns, get_module) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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41 from galaxy_ml.model_validations import _fit_and_score |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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42 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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43 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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44 setattr(_validation, '_fit_and_score', _fit_and_score) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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45 |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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46 N_JOBS = int(os.environ.get('GALAXY_SLOTS', 1)) |
a5aed87b2cc0
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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47 CACHE_DIR = os.path.join(os.getcwd(), 'cached') |
a5aed87b2cc0
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5b2ac730ec6d3b762faa9034eddd19ad1b347476"
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48 del os |
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49 ALLOWED_CALLBACKS = ('EarlyStopping', 'TerminateOnNaN', 'ReduceLROnPlateau', |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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50 'CSVLogger', 'None') |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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51 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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52 warnings.filterwarnings('ignore') |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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53 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
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54 safe_eval = SafeEval() |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 4ed8c4f6ef9ece81797a398b17a99bbaf49a6978
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55 |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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56 input_json_path = sys.argv[1] |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
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57 with open(input_json_path, 'r') as param_handler: |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit f54ff2ba2f8e7542d68966ce5a6b17d7f624ac48
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58 params = json.load(param_handler) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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59 |
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60 ## load estimator |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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61 with open('$infile_estimator', 'rb') as estimator_handler: |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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62 estimator = load_model(estimator_handler) |
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63 |
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64 estimator_params = estimator.get_params() |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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65 |
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66 ## check estimator hyperparameters |
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67 memory = joblib.Memory(location=CACHE_DIR, verbose=0) |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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68 # cache iraps_core fits could increase search speed significantly |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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69 if estimator.__class__.__name__ == 'IRAPSClassifier': |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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70 estimator.set_params(memory=memory) |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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71 else: |
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72 # For iraps buried in pipeline |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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73 for p, v in estimator_params.items(): |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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74 if p.endswith('memory'): |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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75 # for case of `__irapsclassifier__memory` |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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76 if len(p) > 8 and p[:-8].endswith('irapsclassifier'): |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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77 # cache iraps_core fits could increase search |
efbec977a47d
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 60f0fbc0eafd7c11bc60fb6c77f2937782efd8a9-dirty
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78 # speed significantly |
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79 new_params = {p: memory} |
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80 estimator.set_params(**new_params) |
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81 # security reason, we don't want memory being |
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82 # modified unexpectedly |
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83 elif v: |
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84 new_params = {p, None} |
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85 estimator.set_params(**new_params) |
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86 # For now, 1 CPU is suggested for iprasclassifier |
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87 elif p.endswith('n_jobs'): |
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88 new_params = {p: 1} |
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89 estimator.set_params(**new_params) |
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90 # for security reason, types of callback are limited |
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91 elif p.endswith('callbacks'): |
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92 for cb in v: |
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93 cb_type = cb['callback_selection']['callback_type'] |
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94 if cb_type not in ALLOWED_CALLBACKS: |
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95 raise ValueError( |
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96 "Prohibited callback type: %s!" % cb_type) |
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97 |
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98 ## store read dataframe object |
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99 loaded_df = {} |
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100 |
19
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101 #if $input_options.selected_input == 'tabular' |
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102 header = 'infer' if params['input_options']['header1'] else None |
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103 column_option = params['input_options']['column_selector_options_1']['selected_column_selector_option'] |
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104 if column_option in ['by_index_number', 'all_but_by_index_number', 'by_header_name', 'all_but_by_header_name']: |
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105 c = params['input_options']['column_selector_options_1']['col1'] |
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106 else: |
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107 c = None |
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108 infile1 = '$input_options.infile1' |
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109 df_key = infile1 + repr(header) |
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110 df = pd.read_csv(infile1, sep='\t', header=header, parse_dates=True) |
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111 loaded_df[df_key] = df |
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112 X = read_columns(df, c=c, c_option=column_option).astype(float) |
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113 |
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114 #elif $input_options.selected_input == 'sparse': |
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115 X = mmread('$input_options.infile1') |
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116 |
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117 #elif $input_options.selected_input == 'seq_fasta' |
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118 fasta_path = '$input_options.fasta_path' |
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119 pyfaidx = get_module('pyfaidx') |
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120 sequences = pyfaidx.Fasta(fasta_path) |
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121 n_seqs = len(sequences.keys()) |
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122 X = np.arange(n_seqs)[:, np.newaxis] |
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123 for param in estimator_params.keys(): |
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124 if param.endswith('fasta_path'): |
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125 estimator.set_params( |
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126 **{param: fasta_path}) |
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127 break |
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128 else: |
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129 raise ValueError( |
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130 "The selected estimator doesn't support " |
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131 "fasta file input! Please consider using " |
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132 "KerasGBatchClassifier with " |
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133 "FastaDNABatchGenerator/FastaProteinBatchGenerator " |
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134 "or having GenomeOneHotEncoder/ProteinOneHotEncoder " |
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135 "in pipeline!") |
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136 #elif $input_options.selected_input == 'refseq_and_interval' |
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137 ref_seq = '$input_options.ref_genome_file' |
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138 intervals = '$input_options.interval_file' |
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139 targets = __import__('os').path.join(__import__('os').getcwd(), |
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140 '${target_file.element_identifier}.gz') |
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141 path_params = { |
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142 'data_batch_generator__ref_genome_path': ref_seq, |
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143 'data_batch_generator__intervals_path': intervals, |
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144 'data_batch_generator__target_path': targets |
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145 } |
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146 estimator.set_params(**path_params) |
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147 n_intervals = sum(1 for line in open(intervals)) |
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148 X = np.arange(n_intervals)[:, np.newaxis] |
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149 #end if |
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150 |
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151 header = 'infer' if params['input_options']['header2'] else None |
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152 column_option = params['input_options']['column_selector_options_2']['selected_column_selector_option2'] |
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153 if column_option in ['by_index_number', 'all_but_by_index_number', 'by_header_name', 'all_but_by_header_name']: |
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154 c = params['input_options']['column_selector_options_2']['col2'] |
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155 else: |
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156 c = None |
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157 infile2 = '$input_options.infile2' |
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158 df_key = infile2 + repr(header) |
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159 if df_key in loaded_df: |
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160 infile2 = loaded_df[df_key] |
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161 else: |
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162 infile2 = pd.read_csv(infile2, sep='\t', header=header, parse_dates=True) |
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163 loaded_df[df_key] = infile2 |
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164 y = read_columns( |
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165 infile2, |
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166 c = c, |
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167 c_option = column_option, |
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168 sep='\t', |
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169 header=header, |
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170 parse_dates=True) |
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171 if len(y.shape) == 2 and y.shape[1] == 1: |
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172 y = y.ravel() |
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173 #if $input_options.selected_input == 'refseq_and_interval' |
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174 estimator.set_params( |
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175 data_batch_generator__features=y.ravel().tolist()) |
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176 y = None |
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177 #end if |
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178 |
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179 ## handle options |
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180 options = params['model_validation_functions']['options'] |
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181 |
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182 #if $model_validation_functions.options.cv_selector.selected_cv\ |
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183 in ['GroupKFold', 'GroupShuffleSplit', 'LeaveOneGroupOut', 'LeavePGroupsOut']: |
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184 infile_g = '$model_validation_functions.options.cv_selector.groups_selector.infile_g' |
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185 header = 'infer' if options['cv_selector']['groups_selector']['header_g'] else None |
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186 column_option = (options['cv_selector']['groups_selector']['column_selector_options_g'] |
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187 ['selected_column_selector_option_g']) |
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188 if column_option in ['by_index_number', 'all_but_by_index_number', |
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189 'by_header_name', 'all_but_by_header_name']: |
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190 c = (options['cv_selector']['groups_selector']['column_selector_options_g']['col_g']) |
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191 else: |
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192 c = None |
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193 df_key = infile_g + repr(header) |
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194 if df_key in loaded_df: |
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195 infile_g = loaded_df[df_key] |
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196 groups = read_columns(infile_g, c=c, c_option=column_option, |
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197 sep='\t', header=header, parse_dates=True) |
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198 groups = groups.ravel() |
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199 options['cv_selector']['groups_selector'] = groups |
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200 #end if |
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201 |
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202 ## del loaded_df |
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203 del loaded_df |
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204 |
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205 splitter, groups = get_cv( options.pop('cv_selector') ) |
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206 options['cv'] = splitter |
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207 options['groups'] = groups |
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208 options['n_jobs'] = N_JOBS |
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209 if 'scoring' in options: |
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210 primary_scoring = options['scoring']['primary_scoring'] |
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211 options['scoring'] = get_scoring(options['scoring']) |
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212 if 'pre_dispatch' in options and options['pre_dispatch'] == '': |
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213 options['pre_dispatch'] = None |
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214 |
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215 ## Set up validator, run estimator through validator and return results. |
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216 |
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217 validator = params['model_validation_functions']['selected_function'] |
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218 validator = getattr(_validation, validator) |
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219 |
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220 selected_function = params['model_validation_functions']['selected_function'] |
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221 |
2
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222 if selected_function == 'cross_validate': |
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223 res = validator(estimator, X, y, **options) |
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224 stat = {} |
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225 for k, v in res.items(): |
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226 if k.startswith('test'): |
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227 stat['mean_' + k] = np.mean(v) |
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228 stat['std_' + k] = np.std(v) |
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229 res.update(stat) |
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230 rval = pd.DataFrame(res) |
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231 rval = rval[sorted(rval.columns)] |
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232 elif selected_function == 'cross_val_predict': |
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233 predicted = validator(estimator, X, y, **options) |
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234 if len(predicted.shape) == 1: |
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235 rval = pd.DataFrame(predicted, columns=['Predicted']) |
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236 else: |
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237 rval = pd.DataFrame(predicted) |
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238 elif selected_function == 'learning_curve': |
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239 try: |
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240 train_sizes = safe_eval(options['train_sizes']) |
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241 except Exception: |
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242 sys.exit("Unsupported train_sizes input! Supports int/float in tuple and array-like structure.") |
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243 if type(train_sizes) is tuple: |
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244 train_sizes = np.linspace(*train_sizes) |
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245 options['train_sizes'] = train_sizes |
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246 train_sizes_abs, train_scores, test_scores = validator(estimator, X, y, **options) |
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247 rval = pd.DataFrame(dict( |
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248 train_sizes_abs = train_sizes_abs, |
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249 mean_train_scores = np.mean(train_scores, axis=1), |
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250 std_train_scores = np.std(train_scores, axis=1), |
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251 mean_test_scores = np.mean(test_scores, axis=1), |
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252 std_test_scores = np.std(test_scores, axis=1))) |
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253 rval = rval[['train_sizes_abs', 'mean_train_scores', 'std_train_scores', |
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254 'mean_test_scores', 'std_test_scores']] |
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255 elif selected_function == 'permutation_test_score': |
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256 score, permutation_scores, pvalue = validator(estimator, X, y, **options) |
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257 permutation_scores_df = pd.DataFrame(dict( |
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258 permutation_scores = permutation_scores)) |
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259 score_df = pd.DataFrame(dict( |
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260 score = [score], |
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261 pvalue = [pvalue])) |
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262 rval = pd.concat([score_df[['score', 'pvalue']], permutation_scores_df], axis=1) |
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263 |
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264 rval.to_csv(path_or_buf='$outfile', sep='\t', header=True, index=False) |
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265 |
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266 ]]> |
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267 </configfile> |
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268 </configfiles> |
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269 <inputs> |
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270 <param name="infile_estimator" type="data" format="zip" label="Choose the dataset containing model/pipeline object" /> |
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271 <conditional name="model_validation_functions"> |
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272 <param name="selected_function" type="select" label="Select a model validation function"> |
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273 <option value="cross_validate">cross_validate - Evaluate metric(s) by cross-validation and also record fit/score times</option> |
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274 <option value="cross_val_predict">cross_val_predict - Generate cross-validated estimates for each input data point</option> |
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275 <option value="learning_curve">learning_curve - Learning curve</option> |
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276 <option value="permutation_test_score">permutation_test_score - Evaluate the significance of a cross-validated score with permutations</option> |
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277 <option value="validation_curve">validation_curve - Use grid search with one parameter instead</option> |
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278 </param> |
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279 <when value="cross_validate"> |
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280 <section name="options" title="Other Options" expanded="false"> |
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281 <expand macro="scoring_selection" /> |
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282 <expand macro="model_validation_common_options" /> |
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283 <param argument="return_train_score" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" help="Whether to include train scores." /> |
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284 <!--param argument="return_estimator" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" help="Whether to return the estimators fitted on each split."/> --> |
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285 <!--param argument="error_score" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Raise fit error:" help="If false, the metric score is assigned to NaN if an error occurs in estimator fitting and FitFailedWarning is raised."/> --> |
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286 <!--fit_params--> |
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287 <expand macro="pre_dispatch" /> |
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288 </section> |
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289 </when> |
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290 <when value="cross_val_predict"> |
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291 <section name="options" title="Other Options" expanded="false"> |
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292 <expand macro="model_validation_common_options" /> |
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293 <!--fit_params--> |
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294 <expand macro="pre_dispatch" value="2*n_jobs’" help="Controls the number of jobs that get dispatched during parallel execution" /> |
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295 <param argument="method" type="select" label="Invokes the passed method name of the passed estimator"> |
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296 <option value="predict" selected="true">predict</option> |
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297 <option value="predict_proba">predict_proba</option> |
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298 </param> |
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299 </section> |
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300 </when> |
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301 <when value="learning_curve"> |
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302 <section name="options" title="Other Options" expanded="false"> |
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303 <expand macro="scoring_selection" /> |
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304 <expand macro="model_validation_common_options" /> |
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305 <param argument="train_sizes" type="text" value="(0.1, 1.0, 5)" label="train_sizes" help="Relative or absolute numbers of training examples that will be used to generate the learning curve. Supports 1) tuple, to be evaled by np.linspace, e.g. (0.1, 1.0, 5); 2) array-like, e.g. [0.1 , 0.325, 0.55 , 0.775, 1.]"> |
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306 <sanitizer> |
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307 <valid initial="default"> |
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308 <add value="[" /> |
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309 <add value="]" /> |
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310 </valid> |
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311 </sanitizer> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
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312 </param> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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313 <param argument="exploit_incremental_learning" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" help="Whether to apply incremental learning to speed up fitting of the estimator if supported" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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314 <expand macro="pre_dispatch" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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|
315 <expand macro="shuffle" checked="false" label="shuffle" help="Whether to shuffle training data before taking prefixes" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
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316 <expand macro="random_state" help_text="If int, the seed used by the random number generator. Used when `shuffle` is True" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
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317 </section> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
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318 </when> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
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319 <when value="permutation_test_score"> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
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320 <section name="options" title="Other Options" expanded="false"> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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321 <expand macro="scoring_selection" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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322 <expand macro="model_validation_common_options" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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|
323 <param name="n_permutations" type="integer" value="100" optional="true" label="n_permutations" help="Number of times to permute y" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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changeset
|
324 <expand macro="random_state" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
325 </section> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
326 </when> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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diff
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|
327 <when value="validation_curve" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
328 </conditional> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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|
329 <expand macro="sl_mixed_input_plus_sequence" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
330 </inputs> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
331 <outputs> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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|
332 <data format="tabular" name="outfile" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
333 </outputs> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
334 <tests> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
335 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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|
336 <param name="infile_estimator" value="pipeline02" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
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|
337 <param name="selected_function" value="cross_validate" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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338 <param name="return_train_score" value="True" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
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339 <param name="infile1" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
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|
340 <param name="col1" value="1,2,3,4,5" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
341 <param name="infile2" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
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|
342 <param name="col2" value="6" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
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|
343 <output name="outfile"> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
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|
344 <assert_contents> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
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|
345 <has_n_columns n="6" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
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|
346 <has_text text="0.9999961390418067" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
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|
347 <has_text text="0.9944541531269271" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
348 <has_text text="0.9999193322454393" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
349 </assert_contents> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
350 </output> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
351 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
352 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
353 <param name="infile_estimator" value="pipeline02" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
354 <param name="selected_function" value="cross_val_predict" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
355 <param name="infile1" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
356 <param name="col1" value="1,2,3,4,5" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
357 <param name="infile2" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
358 <param name="col2" value="6" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
359 <output name="outfile" file="mv_result02.tabular" lines_diff="14" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
360 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
361 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
362 <param name="infile_estimator" value="pipeline05" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
363 <param name="selected_function" value="learning_curve" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
364 <param name="infile1" value="regression_X.tabular" ftype="tabular" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
365 <param name="header1" value="true" /> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
366 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
367 <param name="infile2" value="regression_y.tabular" ftype="tabular" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
368 <param name="header2" value="true" /> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
369 <param name="col2" value="1" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
370 <output name="outfile" file="mv_result03.tabular" /> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
371 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
372 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
373 <param name="infile_estimator" value="pipeline05" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
374 <param name="selected_function" value="permutation_test_score" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
375 <param name="infile1" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
376 <param name="col1" value="1,2,3,4,5" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
377 <param name="infile2" value="regression_train.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
378 <param name="col2" value="6" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
379 <output name="outfile"> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
380 <assert_contents> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
381 <has_n_columns n="3" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
changeset
|
382 <has_text text="0.25697059258228816" /> |
17
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
383 </assert_contents> |
cf9aa11b91c8
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
bgruening
parents:
16
diff
changeset
|
384 </output> |
0
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
385 </test> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
bgruening
parents:
diff
changeset
|
386 <test> |
28
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
bgruening
parents:
24
diff
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387 <param name="infile_estimator" value="pipeline05" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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388 <param name="selected_function" value="cross_val_predict" /> |
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389 <section name="groups_selector"> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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390 <param name="infile_groups" value="regression_y.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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391 <param name="header_g" value="true" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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392 <param name="selected_column_selector_option_g" value="by_index_number" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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393 <param name="col_g" value="1" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ab963ec9498bd05d2fb2f24f75adb2fccae7958c
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394 </section> |
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395 <param name="selected_cv" value="GroupKFold" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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396 <param name="infile1" value="regression_X.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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397 <param name="header1" value="true" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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398 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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399 <param name="infile2" value="regression_y.tabular" ftype="tabular" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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400 <param name="header2" value="true" /> |
9b017b0da56e
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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401 <param name="col2" value="1" /> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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402 <output name="outfile" file="mv_result05.tabular" /> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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403 </test> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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404 </tests> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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405 <help> |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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406 <![CDATA[ |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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407 **What it does** |
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408 This tool includes model validation functions to evaluate estimator performance in the cross-validation approach. This tool is based on |
333507faecab
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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409 sklearn.model_selection package. |
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410 For information about model validation functions and their parameter settings please refer to `Scikit-learn model_selection`_. |
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411 |
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412 .. _`Scikit-learn model_selection`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.model_selection |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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413 ]]> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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414 </help> |
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415 <expand macro="sklearn_citation"> |
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416 <expand macro="skrebate_citation" /> |
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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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417 <expand macro="xgboost_citation" /> |
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418 </expand> |
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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 2e1e78576b38110cf5b1f2ed83b08b9c3a6cbfee
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419 </tool> |