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annotate pipeline.xml @ 0:f8b431b981fa draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
author bgruening
date Sat, 04 Aug 2018 12:14:28 -0400
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children ddd8c51b7302
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f8b431b981fa planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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1 <tool id="sklearn_build_pipeline" name="Pipeline Builder" version="@VERSION@">
f8b431b981fa planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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2 <description>constructs a list of transforms and a final estimator</description>
f8b431b981fa planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 76583c1fcd9d06a4679cc46ffaee44117b9e22cd
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3 <macros>
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4 <import>main_macros.xml</import>
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5 </macros>
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6 <expand macro="python_requirements"/>
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7 <expand macro="macro_stdio"/>
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8 <version_command>echo "@VERSION@"</version_command>
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9 <command>
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10 <![CDATA[
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11 python "$sklearn_pipeline_script" '$inputs'
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12 ]]>
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13 </command>
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14 <configfiles>
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15 <inputs name="inputs" />
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16 <configfile name="sklearn_pipeline_script">
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17 <![CDATA[
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18 import sys
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19 import json
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20 import pickle
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21 import pprint
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22 import xgboost
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23 import ast
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24 import sklearn.feature_selection
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25 from sklearn import ( preprocessing, svm, linear_model, ensemble, naive_bayes,
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26 tree, neighbors, decomposition, kernel_approximation, cluster)
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27 from sklearn.pipeline import Pipeline
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28
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29 @GET_ESTIMATOR_FUNCTION@
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30 @FEATURE_SELECTOR_FUNCTION@
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31
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32 input_json_path = sys.argv[1]
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33 with open(input_json_path, "r") as param_handler:
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34 params = json.load(param_handler)
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35
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36 pipeline_steps = []
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37
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38 def get_component(input_json, check_none=False):
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39 if input_json['component_type'] == 'None':
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40 if not check_none:
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41 return
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42 else:
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43 sys.exit("The pre-processing component type can't be None when the number of components is greater than 1.")
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44 if input_json['component_type'] == 'pre_processor':
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45 preprocessor = input_json["pre_processors"]["selected_pre_processor"]
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46 pre_processor_options = input_json["pre_processors"]["options"]
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47 my_class = getattr(preprocessing, preprocessor)
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48 return my_class(**pre_processor_options)
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49 if input_json['component_type'] == 'feature_selection':
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50 fs_obj = feature_selector(input_json['fs_algorithm_selector'])
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51 return fs_obj
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52 if input_json['component_type'] == 'decomposition':
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53 algorithm = input_json['matrix_decomposition_selector']['select_algorithm']
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54 obj = getattr(decomposition, algorithm)()
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55 options = input_json['matrix_decomposition_selector']['text_params'].strip()
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56 if options != "":
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57 options = ast.literal_eval('{' + options + '}')
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58 obj.set_params(**options)
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59 return obj
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60 if input_json['component_type'] == 'kernel_approximation':
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61 algorithm = input_json['kernel_approximation_selector']['select_algorithm']
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62 obj = getattr(kernel_approximation, algorithm)()
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63 options = input_json['kernel_approximation_selector']['text_params'].strip()
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64 if options != "":
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65 options = ast.literal_eval('{' + options + '}')
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66 obj.set_params(**options)
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67 return obj
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68 if input_json['component_type'] == 'FeatureAgglomeration':
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69 algorithm = input_json['FeatureAgglomeration_selector']['select_algorithm']
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70 obj = getattr(cluster, algorithm)()
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71 options = input_json['FeatureAgglomeration_selector']['text_params'].strip()
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72 if options != "":
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73 options = ast.literal_eval('{' + options + '}')
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74 obj.set_params(**options)
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75 return obj
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76 if len(params['pipeline_component']) == 1:
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77 step_obj = get_component( params['pipeline_component'][0]['component_selector'])
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78 if step_obj:
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79 pipeline_steps.append( ('preprocessing_1', step_obj) )
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80 else:
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81 for i, c in enumerate(params['pipeline_component']):
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82 step_obj = get_component( c['component_selector'], check_none=True )
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83 pipeline_steps.append( ('preprocessing_' + str(i+1), step_obj) )
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84
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85 # Set up final estimator and add to pipeline.
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86 estimator_json = params["final_estimator"]['estimator_selector']
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87 estimator = get_estimator(estimator_json)
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88
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89 pipeline_steps.append( ('estimator', estimator) )
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90
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91 pipeline = Pipeline(pipeline_steps)
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92 pprint.pprint(pipeline.named_steps)
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93
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94 with open("$outfile", 'wb') as out_handler:
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95 pickle.dump(pipeline, out_handler, pickle.HIGHEST_PROTOCOL)
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96
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97 ]]>
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98 </configfile>
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99 </configfiles>
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100 <inputs>
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101 <repeat name="pipeline_component" min="1" max="5" title="Pre-processing step">
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102 <conditional name="component_selector">
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103 <param name="component_type" type="select" label="Choose the type of transformation:">
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104 <option value="none" selected="true">None</option>
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105 <option value="pre_processor">Sklearn Preprocessor</option>
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106 <option value="feature_selection">Feature Selection</option>
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107 <option value="decomposition">Matrix Decomposition</option>
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108 <option value="kernel_approximation">Kernel Approximation</option>
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109 <option value="FeatureAgglomeration">Agglomerate Features</option>
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110 </param>
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111 <when value="none"/>
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112 <when value="pre_processor">
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113 <conditional name="pre_processors">
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114 <expand macro="sparse_preprocessors_ext" />
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115 <expand macro="sparse_preprocessor_options_ext" />
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116 </conditional>
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117 </when>
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118 <when value="feature_selection">
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119 <expand macro="feature_selection_all">
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120 <expand macro="fs_selectfrommodel_no_prefitted"/>
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121 </expand>
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122 </when>
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123 <when value="decomposition">
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124 <expand macro="matrix_decomposition_all"/>
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125 </when>
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126 <when value="kernel_approximation">
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127 <expand macro="kernel_approximation_all"/>
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128 </when>
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129 <when value="FeatureAgglomeration">
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130 <expand macro="FeatureAgglomeration"/>
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131 </when>
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132 </conditional>
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133 </repeat>
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134 <section name="final_estimator" title="Final Estimator" expanded="true">
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135 <expand macro="estimator_selector_all" />
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136 </section>
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137 </inputs>
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138 <outputs>
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139 <data format="zip" name="outfile"/>
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140 </outputs>
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141 <tests>
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142 <test>
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143 <repeat name="pipeline_component">
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144 <conditional name="component_selector">
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145 <param name="component_type" value="pre_processor"/>
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146 <conditional name="pre_processors">
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147 <param name="selected_pre_processor" value="RobustScaler"/>
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148 </conditional>
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149 </conditional>
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150 </repeat>
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151 <repeat name="pipeline_component">
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152 <conditional name="component_selector">
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153 <param name="component_type" value="feature_selection"/>
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154 <conditional name="fs_algorithm_selector">
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155 <param name="selected_algorithm" value="SelectKBest"/>
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156 <param name="score_func" value="f_classif"/>
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157 </conditional>
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158 </conditional>
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159 </repeat>
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160 <param name="selected_module" value="svm"/>
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161 <param name="selected_estimator" value="SVR"/>
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162 <param name="text_params" value="'kernel': 'linear'"/>
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163 <output name="outfile" file="pipeline01" compare="sim_size" delta="1"/>
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164 </test>
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165 <test>
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166 <conditional name="component_selector">
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167 <param name="component_type" value="pre_processor"/>
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168 <conditional name="pre_processors">
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169 <param name="selected_pre_processor" value="RobustScaler"/>
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170 </conditional>
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171 </conditional>
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172 <param name="selected_module" value="linear_model"/>
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173 <param name="selected_estimator" value="LassoCV"/>
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174 <output name="outfile" file="pipeline02" compare="sim_size" delta="1"/>
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175 </test>
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176 <test>
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177 <conditional name="component_selector">
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178 <param name="component_type" value="pre_processor"/>
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179 <conditional name="pre_processors">
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180 <param name="selected_pre_processor" value="RobustScaler"/>
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181 </conditional>
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182 </conditional>
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183 <param name="selected_module" value="xgboost"/>
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184 <param name="selected_estimator" value="XGBClassifier"/>
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185 <output name="outfile" file="pipeline03" compare="sim_size" delta="1"/>
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186 </test>
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187 <test>
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188 <conditional name="component_selector">
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189 <param name="component_type" value="feature_selection"/>
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190 <conditional name="fs_algorithm_selector">
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191 <param name="selected_algorithm" value="SelectFromModel"/>
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192 <conditional name="model_inputter">
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193 <conditional name="estimator_selector">
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194 <param name="selected_module" value="ensemble"/>
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195 <param name="selected_estimator" value="AdaBoostClassifier"/>
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196 </conditional>
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197 </conditional>
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198 </conditional>
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199 </conditional>
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200 <section name="final_estimator">
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201 <param name="selected_module" value="svm"/>
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202 <param name="selected_estimator" value="LinearSVC"/>
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203 </section>
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204 <output name="outfile" file="pipeline04" compare="sim_size" delta="1"/>
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205 </test>
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206 <test>
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207 <conditional name="component_selector">
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208 <param name="component_type" value="None"/>
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209 </conditional>
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210 <param name="selected_module" value="ensemble"/>
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211 <param name="selected_estimator" value="RandomForestRegressor"/>
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212 <param name="text_params" value="'n_estimators': 100, 'random_state': 42"/>
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213 <output name="outfile" file="pipeline05" compare="sim_size" delta="1"/>
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214 </test>
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215 <test>
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216 <conditional name="component_selector">
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217 <param name="component_type" value="decomposition"/>
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218 <conditional name="matrix_decomposition_selector">
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219 <param name="select_algorithm" value="PCA"/>
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220 </conditional>
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221 </conditional>
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222 <param name="selected_module" value="ensemble"/>
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223 <param name="selected_estimator" value="AdaBoostRegressor"/>
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224 <output name="outfile" file="pipeline06" compare="sim_size" delta="1"/>
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225 </test>
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226 <test>
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227 <conditional name="component_selector">
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228 <param name="component_type" value="kernel_approximation"/>
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229 <conditional name="kernel_approximation_selector">
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230 <param name="select_algorithm" value="RBFSampler"/>
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231 <param name="text_params" value="'n_components': 10, 'gamma': 2.0"/>
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232 </conditional>
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233 </conditional>
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234 <param name="selected_module" value="ensemble"/>
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235 <param name="selected_estimator" value="AdaBoostClassifier"/>
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236 <output name="outfile" file="pipeline07" compare="sim_size" delta="1"/>
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237 </test>
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238 <test>
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239 <conditional name="component_selector">
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240 <param name="component_type" value="FeatureAgglomeration"/>
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241 <conditional name="FeatureAgglomeration_selector">
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242 <param name="select_algorithm" value="FeatureAgglomeration"/>
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243 <param name="text_params" value="'n_clusters': 3, 'affinity': 'euclidean'"/>
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244 </conditional>
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245 </conditional>
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246 <param name="selected_module" value="ensemble"/>
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247 <param name="selected_estimator" value="AdaBoostClassifier"/>
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248 <output name="outfile" file="pipeline08" compare="sim_size" delta="1"/>
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249 </test>
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250 </tests>
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251 <help>
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252 <![CDATA[
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253 **What it does**
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254 Constructs a pipeline that contains a list of transfroms and a final estimator. Pipeline assembles several steps
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255 that can be cross-validated together while setting different parameters.
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256 please refer to `Scikit-learn pipeline Pipeline`_.
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257
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258 **Pre-processing components** allow None, one or a combination of up to 5 transformations from `sklearn.preprocessing`_, `feature_selection`_, `decomposition`_, `kernel_approximation`_ and/or `cluster.FeatureAgglomeration`_.
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259
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260 **Estimator** selector supports estimators from `xgboost`_ and many scikit-learn modules, including `svm`_, `linear_model`_, `ensemble`_, `naive_bayes`_, `tree`_ and `neighbors`_.
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261
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262
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263 .. _`Scikit-learn pipeline Pipeline`: http://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html
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264 .. _`svm`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.svm
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265 .. _`linear_model`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.linear_model
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266 .. _`ensemble`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.ensemble
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267 .. _`naive_bayes`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.naive_bayes
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268 .. _`tree`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.tree
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269 .. _`neighbors`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.neighbors
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270 .. _`xgboost`: https://xgboost.readthedocs.io/en/latest/python/python_api.html
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271
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272 .. _`sklearn.preprocessing`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.preprocessing
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273 .. _`feature_selection`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.feature_selection
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274 .. _`decomposition`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.decomposition
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275 .. _`kernel_approximation`: http://scikit-learn.org/stable/modules/classes.html#module-sklearn.kernel_approximation
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276 .. _`cluster.FeatureAgglomeration`: http://scikit-learn.org/stable/modules/generated/sklearn.cluster.FeatureAgglomeration.html
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277
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278 ]]>
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279 </help>
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280 <expand macro="sklearn_citation"/>
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281 </tool>