Mercurial > repos > bgruening > sklearn_estimator_attributes

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a
author bgruening
date Mon, 02 Oct 2023 08:40:13 +0000
parents dd157beef3e4
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dd157beef3e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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1 <tool id="sklearn_estimator_attributes" name="Estimator attributes" version="@VERSION@" profile="@PROFILE@">
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2 <description>get important attributes from an estimator or scikit object</description>
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3 <macros>
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4 <import>main_macros.xml</import>
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5 </macros>
10
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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>
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10 <![CDATA[
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11 python '$main_script'
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12 ]]>
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13 </command>
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14 <configfiles>
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15 <configfile name="main_script">
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16 <![CDATA[
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17 import json
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18 import pandas
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19 import skrebate
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20 import sys
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21 import warnings
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22 import xgboost
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23 from mlxtend import regressor, classifier
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24 from sklearn import (
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25 cluster, compose, decomposition, ensemble, feature_extraction,
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26 feature_selection, gaussian_process, kernel_approximation, metrics,
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27 model_selection, naive_bayes, neighbors, pipeline, preprocessing,
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28 svm, linear_model, tree, discriminant_analysis)
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29 from imblearn.pipeline import Pipeline as imbPipeline
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30 from sklearn.pipeline import Pipeline
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31
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32 from galaxy_ml.model_persist import load_model_from_h5, dump_model_to_h5
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33 from galaxy_ml.utils import get_search_params
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35 warnings.simplefilter('ignore')
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37 infile_object = '$infile_object'
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38 attribute = '$attribute_type'
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39
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40 est_obj = load_model_from_h5(infile_object)
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41
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42 if attribute == 'get_params':
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43 ## get_params()
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44 results = get_search_params(est_obj)
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45 df = pandas.DataFrame(results, columns=['', 'Parameter', 'Value'])
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46 df.to_csv('$outfile', sep='\t', index=False)
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47 elif attribute == 'final_estimator':
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48 res = est_obj.steps[-1][-1]
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49 print(repr(res))
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50 dump_model_to_h5(res, '$outfile')
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51 elif attribute in ['best_estimator_', 'init_', 'classifier_', 'regressor_']:
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52 res = getattr(est_obj, attribute)
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53 print(repr(res))
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54 dump_model_to_h5(res, '$outfile')
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55 elif attribute in ['oob_score_', 'best_score_', 'n_features_in']:
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56 res = getattr(est_obj, attribute)
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57 res = pandas.DataFrame([res], columns=[attribute])
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58 res.to_csv('$outfile', sep='\t', index=False)
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59 elif attribute in ['best_params_', 'named_steps']:
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60 res = getattr(est_obj, attribute)
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61 with open('$outfile', 'w') as f:
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62 f.write(repr(res))
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63 elif attribute == 'cv_results_':
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64 res = pandas.DataFrame(est_obj.cv_results_)
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65 res = res[sorted(res.columns)]
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66 res.to_csv('$outfile', sep='\t', index=False)
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67 else:
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68 if attribute == 'get_signature':
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69 res = est_obj.get_signature()
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70 else:
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71 res = getattr(est_obj, attribute)
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72 columns = []
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73 if res.ndim == 1 or res.shape[-1] == 1:
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74 columns = [attribute]
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75 else:
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76 for i in range(res.shape[-1]):
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77 columns.append(attribute + '_' + str(i))
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78 res = pandas.DataFrame(res, columns=columns)
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79 res.to_csv('$outfile', sep='\t', index=False)
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80
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81 ]]>
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82 </configfile>
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83 </configfiles>
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84 <inputs>
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85 <param name="infile_object" type="data" format="h5mlm" label="Choose the dataset containing estimator/pipeline object" />
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86 <param name="attribute_type" type="select" label="Select an attribute retrival type">
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87 <option value="get_params" selected="true">Estimator - get_params()</option>
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88 <option value="feature_importances_" >Fitted estimator - feature_importances_ </option>
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89 <option value="coef_">Fitted estimator - coef_ </option>
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90 <option value="train_score_">Fitted estimator - train_score_ </option>
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91 <option value="oob_score_">Fitted estimator - oob_score_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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92 <option value="init_">Fitted estimator - init_ </option>
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93 <option value="classifier_">Fitted BinarizeTargetClassifier - classifier_</option>
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94 <option value="regressor_">Fitted BinarizeTargetRegressor - regressor_</option>
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95 <option value="get_signature">Fitted IRAPSClassifier - get_signature</option>
0
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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96 <option value="named_steps">Pipeline - named_steps </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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97 <option value="final_estimator">Pipeline - final_estimator </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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98 <option value="cv_results_">SearchCV - cv_results_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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99 <option value="best_estimator_">SearchCV - best_estimator_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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100 <option value="best_score_">SearchCV - best_score_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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101 <option value="best_params_">SearchCV - best_params_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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102 <option value="scores_">Feature_selection - scores_ </option>
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103 <option value="pvalues_">Feature_selection - pvalues_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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104 <option value="ranking_">Feature_selection - ranking_ </option>
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105 <option value="n_features_in">Feature_selection - n_features_in </option>
0
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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106 <option value="grid_scores_">Feature_selection - grid_scores_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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107 </param>
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108 </inputs>
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109 <outputs>
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110 <data format="tabular" name="outfile" label="${attribute_type} from ${on_string}">
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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111 <change_format>
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112 <when input="attribute_type" value="named_steps" format="txt" />
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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113 <when input="attribute_type" value="best_params_" format="txt" />
16
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114 <when input="attribute_type" value="final_estimator" format="h5mlm" />
dd157beef3e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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115 <when input="attribute_type" value="best_estimator_" format="h5mlm" />
dd157beef3e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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116 <when input="attribute_type" value="init_" format="h5mlm" />
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117 <when input="attribute_type" value="classifier_" format="h5mlm" />
dd157beef3e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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118 <when input="attribute_type" value="regressor_" format="h5mlm" />
0
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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119 </change_format>
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120 </data>
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121 </outputs>
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122 <tests>
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123 <test>
16
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124 <param name="infile_object" value="GridSearchCV01.h5mlm" ftype="h5mlm" />
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125 <param name="attribute_type" value="best_score_" />
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126 <output name="outfile" file="best_score_.tabular" />
0
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127 </test>
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128 <test>
16
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129 <param name="infile_object" value="GridSearchCV01.h5mlm" ftype="h5mlm" />
10
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130 <param name="attribute_type" value="best_params_" />
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131 <output name="outfile" file="best_params_.txt" />
0
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132 </test>
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133 <test>
16
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134 <param name="infile_object" value="GridSearchCV01.h5mlm" ftype="h5mlm" />
10
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135 <param name="attribute_type" value="best_estimator_" />
16
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136 <output name="outfile" file="best_estimator_.h5mlm" compare="sim_size" delta="10" />
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137 </test>
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138 <test>
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139 <param name="infile_object" value="searchCV01" ftype="h5mlm" />
dd157beef3e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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140 <param name="attribute_type" value="final_estimator" />
dd157beef3e4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
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141 <output name="outfile" file="final_estimator.h5mlm" compare="sim_size" delta="10" />
0
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142 </test>
10
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143 <test>
16
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144 <param name="infile_object" value="searchCV01" ftype="h5mlm" />
10
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145 <param name="attribute_type" value="named_steps" />
a0c8fa720406 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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146 <output name="outfile" file="named_steps.txt" compare="sim_size" delta="5" />
0
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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147 </test>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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148 <test>
16
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149 <param name="infile_object" value="best_estimator_.h5mlm" ftype="h5mlm" />
10
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150 <param name="attribute_type" value="feature_importances_" />
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151 <output name="outfile" file="feature_importances_.tabular" />
0
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152 </test>
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153 <test>
16
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154 <param name="infile_object" value="RFE.h5mlm" ftype="h5mlm" />
10
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155 <param name="attribute_type" value="ranking_" />
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156 <output name="outfile" file="ranking_.tabular" />
0
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157 </test>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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158 <test>
16
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159 <param name="infile_object" value="LinearRegression01.h5mlm" ftype="h5mlm" />
10
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160 <param name="attribute_type" value="get_params" />
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161 <output name="outfile" value="get_params.tabular" />
0
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162 </test>
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163 </tests>
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164 <help>
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165 <![CDATA[
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166 **What it does**
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167 Output attribute from an estimator or any scikit object.
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168
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169 Common attributes are :
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170
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171 - ``estimator.`` *feature_importances_*
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172 - ``RFE``. *ranking_*
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173 - ``RFECV``. *grid_scores_*
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174 - ``GridSearchCV``. *best_estimator_*
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175
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176 ]]>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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177 </help>
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178 <expand macro="sklearn_citation">
10
a0c8fa720406 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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179 <expand macro="skrebate_citation" />
a0c8fa720406 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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180 <expand macro="xgboost_citation" />
a0c8fa720406 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
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92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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182 </expand>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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183 </tool>