Mercurial > repos > bgruening > sklearn_estimator_attributes

annotate estimator_attributes.xml @ 1:7105ef44c6ec draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 49522db5f2dc8a571af49e3f38e80c22571068f4
author bgruening
date Tue, 09 Jul 2019 19:13:07 -0400
parents 92918723f751
children 61fec8352927
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92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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1 <tool id="sklearn_estimator_attributes" name="Estimator attributes" version="@VERSION@">
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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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>
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6 <expand macro="python_requirements"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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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[
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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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[
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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17 import json
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18 import pandas
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19 import pickle
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20 import skrebate
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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21 import sys
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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22 import warnings
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23 import xgboost
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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24 from mlxtend import regressor, classifier
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25 from sklearn import (
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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26 cluster, compose, decomposition, ensemble, feature_extraction,
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27 feature_selection, gaussian_process, kernel_approximation, metrics,
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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28 model_selection, naive_bayes, neighbors, pipeline, preprocessing,
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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29 svm, linear_model, tree, discriminant_analysis)
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30 from imblearn.pipeline import Pipeline as imbPipeline
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31 from sklearn.pipeline import Pipeline
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32
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33 sys.path.insert(0, '$__tool_directory__')
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34 from utils import load_model, get_search_params
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35
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36 warnings.simplefilter('ignore')
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37
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38 infile_object = '$infile_object'
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39 attribute = '$attribute_type'
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40
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41 with open(infile_object, 'rb') as f:
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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42 est_obj = load_model(f)
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43
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44 if attribute == 'get_params':
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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45 ## get_params()
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46 results = get_search_params(est_obj)
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47 df = pandas.DataFrame(results, columns=['', 'Parameter', 'Value'])
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48 df.to_csv('$outfile', sep='\t', index=False)
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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49 elif attribute == 'final_estimator':
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50 res = est_obj.steps[-1][-1]
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51 print(repr(res))
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52 with open('$outfile', 'wb') as f:
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53 pickle.dump(res, f, pickle.HIGHEST_PROTOCOL)
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54 elif attribute in ['best_estimator_', 'init_']:
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55 res = getattr(est_obj, attribute)
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56 print(repr(res))
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57 with open('$outfile', 'wb') as f:
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58 pickle.dump(res, f, pickle.HIGHEST_PROTOCOL)
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59 elif attribute in ['oob_score_', 'best_score_', 'n_features_']:
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60 res = getattr(est_obj, attribute)
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61 res = pandas.DataFrame([res], columns=[attribute])
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62 res.to_csv('$outfile', sep='\t', index=False)
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63 elif attribute in ['best_params_', 'named_steps']:
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64 res = getattr(est_obj, attribute)
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65 with open('$outfile', 'w') as f:
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66 f.write(repr(res))
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67 elif attribute == 'cv_results_':
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68 res = pandas.DataFrame(est_obj.cv_results_)
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69 res = res[sorted(res.columns)]
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70 res.to_csv('$outfile', sep='\t', index=False)
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71 else:
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72 res = getattr(est_obj, attribute)
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73 columns = []
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74 if res.ndim == 1 or res.shape[-1] == 1:
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75 columns = [attribute]
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76 else:
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77 for i in range(res.shape[-1]):
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78 columns.append(attribute + '_' + str(i))
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79 res = pandas.DataFrame(res, columns=columns)
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80 res.to_csv('$outfile', sep='\t', index=False)
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81
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82 ]]>
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83 </configfile>
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84 </configfiles>
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85 <inputs>
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86 <param name="infile_object" type="data" format="zip" label="Choose the dataset containing estimator/pipeline object"/>
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87 <param name="attribute_type" type="select" label="Select an attribute retrival type">
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88 <option value="get_params" selected="true">Estimator - get_params()</option>
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89 <option value="feature_importances_" >Fitted estimator - feature_importances_ </option>
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90 <option value="coef_">Fitted estimator - coef_ </option>
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91 <option value="train_score_">Fitted estimator - train_score_ </option>
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92 <option value="oob_score_">Fitted estimator - oob_score_ </option>
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93 <option value="init_">Fitted estimator - init_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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94 <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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95 <option value="final_estimator">Pipeline - final_estimator </option>
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96 <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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97 <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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98 <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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99 <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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100 <option value="scores_">Feature_selection - scores_ </option>
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101 <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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102 <option value="ranking_">Feature_selection - ranking_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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103 <option value="n_features_">Feature_selection - n_features_ </option>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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104 <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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105 </param>
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106 </inputs>
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107 <outputs>
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108 <data format="tabular" name="outfile" label="${attribute_type} from ${on_string}">
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109 <change_format>
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110 <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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111 <when input="attribute_type" value="best_params_" format="txt" />
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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112 <when input="attribute_type" value="final_estimator" format="zip" />
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_estimator_" format="zip" />
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114 <when input="attribute_type" value="init_" format="zip" />
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115 </change_format>
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116 </data>
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117 </outputs>
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118 <tests>
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119 <test>
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120 <param name="infile_object" value="GridSearchCV.zip" ftype="zip"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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121 <param name="attribute_type" value="best_score_"/>
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122 <output name="outfile" file="best_score_.tabular"/>
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123 </test>
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124 <test>
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125 <param name="infile_object" value="GridSearchCV.zip" ftype="zip"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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126 <param name="attribute_type" value="best_params_"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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127 <output name="outfile" file="best_params_.txt"/>
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128 </test>
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129 <test>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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130 <param name="infile_object" value="GridSearchCV.zip" ftype="zip"/>
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131 <param name="attribute_type" value="best_estimator_"/>
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132 <output name="outfile" file="best_estimator_.zip" compare="sim_size" delta="10"/>
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133 </test>
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134 <test>
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135 <param name="infile_object" value="best_estimator_.zip" ftype="zip"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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136 <param name="attribute_type" value="final_estimator"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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137 <output name="outfile" file="final_estimator.zip" compare="sim_size" delta="10"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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138 </test>
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139 <test>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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140 <param name="infile_object" value="best_estimator_.zip" ftype="zip"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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141 <param name="attribute_type" value="named_steps"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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142 <output name="outfile" file="named_steps.txt" compare="sim_size" delta="5"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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143 </test>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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144 <test>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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145 <param name="infile_object" value="final_estimator.zip" ftype="zip"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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146 <param name="attribute_type" value="feature_importances_"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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147 <output name="outfile" file="feature_importances_.tabular"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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148 </test>
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149 <test>
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150 <param name="infile_object" value="RFE.zip" ftype="zip"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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151 <param name="attribute_type" value="ranking_"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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152 <output name="outfile" file="ranking_.tabular"/>
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153 </test>
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154 <test>
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155 <param name="infile_object" value="LinearRegression02.zip" ftype="zip"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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156 <param name="attribute_type" value="get_params"/>
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157 <output name="outfile" value="get_params.tabular"/>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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158 </test>
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159 </tests>
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160 <help>
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161 <![CDATA[
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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162 **What it does**
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163 Output attribute from an estimator or any scikit object.
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164
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165 Common attributes are :
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166
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167 - ``estimator.`` *feature_importances_*
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168 - ``RFE``. *ranking_*
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169 - ``RFECV``. *grid_scores_*
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170 - ``GridSearchCV``. *best_estimator_*
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171
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172 ]]>
92918723f751 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit c0a3a186966888e5787335a7628bf0a4382637e7
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173 </help>
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174 <expand macro="sklearn_citation">
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175 <expand macro="skrebate_citation"/>
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176 <expand macro="xgboost_citation"/>
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177 <expand macro="imblearn_citation"/>
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178 </expand>
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179 </tool>