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annotate feature_selection.xml @ 0:092199a095dd draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
author bgruening
date Thu, 12 Apr 2018 08:23:30 -0400
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children 2eb90e73f0d5
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092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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1 <tool id="sklearn_feature_selection" name="Feature Selection" version="@VERSION@">
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2 <description>module, including univariate filter selection methods and recursive feature elimination algorithm</description>
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3 <macros>
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4 <import>main_macros.xml</import>
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5 </macros>
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6 <expand macro="python_requirements"/>
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7 <expand macro="macro_stdio"/>
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8 <version_command>echo "@VERSION@"</version_command>
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9 <command>
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10 <![CDATA[
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11 python "$feature_selection_script" '$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="feature_selection_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 pandas
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21 import pickle
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22 import numpy as np
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23 import sklearn.feature_selection
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24 from sklearn import svm, linear_model, ensemble
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25
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26 @COLUMNS_FUNCTION@
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27
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28 input_json_path = sys.argv[1]
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29 params = json.load(open(input_json_path, "r"))
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30
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31 input_type = params["input_options"]["selected_input"]
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32 if input_type=="tabular":
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33 header = 'infer' if params["input_options"]["header1"] else None
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34 X = read_columns(
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35 "$input_options.infile1",
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36 "$input_options.col1",
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37 sep='\t',
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38 header=header,
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39 parse_dates=True
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40 )
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41 else:
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42 X = mmread(open("$input_options.infile1", 'r'))
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43
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44 header = 'infer' if params["input_options"]["header2"] else None
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45 y = read_columns(
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46 "$input_options.infile2",
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47 "$input_options.col2",
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48 sep='\t',
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49 header=header,
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50 parse_dates=True
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51 )
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52 y=y.ravel()
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53
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54 selector = params["feature_selection_algorithms"]["selected_algorithm"]
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55 selector = getattr(sklearn.feature_selection, selector)
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56 options = params["feature_selection_algorithms"]["options"]
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57
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58 #if $feature_selection_algorithms.selected_algorithm == 'SelectFromModel':
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59 if not options['threshold'] or options['threshold'] == 'None':
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60 options['threshold'] = None
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61 #if $feature_selection_algorithms.extra_estimator.has_estimator == 'no_load':
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62 fitted_estimator = pickle.load(open("$feature_selection_algorithms.extra_estimator.fitted_estimator", 'r'))
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63 new_selector = selector(fitted_estimator, prefit=True, **options)
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64 #else:
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65 estimator=params["feature_selection_algorithms"]["estimator"]
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66 if params["feature_selection_algorithms"]["extra_estimator"]["has_estimator"]=='no':
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67 estimator=params["feature_selection_algorithms"]["extra_estimator"]["new_estimator"]
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68 estimator=eval(estimator.replace('__dq__', '"').replace("__sq__","'"))
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69 new_selector = selector(estimator, **options)
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70 new_selector.fit(X, y)
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71 #end if
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72
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73 #elif $feature_selection_algorithms.selected_algorithm in ['RFE', 'RFECV']:
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74 if 'scoring' in options and (not options['scoring'] or options['scoring'] == 'None'):
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75 options['scoring'] = None
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76 estimator=params["feature_selection_algorithms"]["estimator"]
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77 if params["feature_selection_algorithms"]["extra_estimator"]["has_estimator"]=='no':
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78 estimator=params["feature_selection_algorithms"]["extra_estimator"]["new_estimator"]
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79 estimator=eval(estimator.replace('__dq__', '"').replace("__sq__","'"))
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80 new_selector = selector(estimator, **options)
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81 new_selector.fit(X, y)
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82
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83 #elif $feature_selection_algorithms.selected_algorithm == "VarianceThreshold":
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84 new_selector = selector(**options)
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85 new_selector.fit(X, y)
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86
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87 #else:
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88 score_func = params["feature_selection_algorithms"]["score_func"]
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89 score_func = getattr(sklearn.feature_selection, score_func)
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90 new_selector = selector(score_func, **options)
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91 new_selector.fit(X, y)
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92 #end if
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93
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94 #if $select_methods.selected_method == "fit_transform":
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95 res = new_selector.transform(X)
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96
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97 #else:
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98 res = new_selector.get_support(params["select_methods"]["indices"])
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99 #end if
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100
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101 res = pandas.DataFrame(res)
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102 res.to_csv(path_or_buf="$outfile", sep='\t', index=False)
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103
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104
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105 ]]>
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106 </configfile>
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107 </configfiles>
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108 <inputs>
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109 <conditional name="feature_selection_algorithms">
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110 <param name="selected_algorithm" type="select" label="Select a feature selection algorithm">
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111 <option value="SelectFromModel" selected="true">SelectFromModel - Meta-transformer for selecting features based on importance weights</option>
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112 <option value="GenericUnivariateSelect" selected="true">GenericUnivariateSelect - Univariate feature selector with configurable strategy</option>
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113 <option value="SelectPercentile">SelectPercentile - Select features according to a percentile of the highest scores</option>
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114 <option value="SelectKBest">SelectKBest - Select features according to the k highest scores</option>
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115 <option value="SelectFpr">SelectFpr - Filter: Select the p-values below alpha based on a FPR test</option>
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116 <option value="SelectFdr">SelectFdr - Filter: Select the p-values for an estimated false discovery rate</option>
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117 <option value="SelectFwe">SelectFwe - Filter: Select the p-values corresponding to Family-wise error rate</option>
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118 <option value="RFE">RFE - Feature ranking with recursive feature elimination</option>
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119 <option value="RFECV">RFECV - Feature ranking with recursive feature elimination and cross-validated selection of the best number of features</option>
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120 <option value="VarianceThreshold">VarianceThreshold - Feature selector that removes all low-variance features</option>
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121 <!--option value="chi2">Compute chi-squared stats between each non-negative feature and class</option-->
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122 <!--option value="f_classif">Compute the ANOVA F-value for the provided sample</option-->
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123 <!--option value="f_regression">Univariate linear regression tests</option-->
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124 <!--option value="mutual_info_classif">Estimate mutual information for a discrete target variable</option-->
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125 <!--option value="mutual_info_regression">Estimate mutual information for a continuous target variable</option-->
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126 </param>
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127 <when value="SelectFromModel">
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128 <expand macro="feature_selection_estimator" />
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129 <conditional name="extra_estimator">
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130 <expand macro="feature_selection_extra_estimator" >
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131 <option value="no_load">No, I will load a prefitted estimator</option>
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132 </expand>
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133 <expand macro="feature_selection_estimator_choices" >
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134 <when value="no_load">
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135 <param name="fitted_estimator" type="data" format='zip' label="Load a prefitted estimator" />
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136 </when>
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137 </expand>
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138 </conditional>
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139 <section name="options" title="Other Options" expanded="True">
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140 <param argument="threshold" type="text" value="" optional="true" label="threshold" help="The threshold value to use for feature selection. e.g. 'mean', 'median', '1.25*mean'." />
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141 <param argument="norm_order" type="integer" value="1" label="norm_order" help="Order of the norm used to filter the vectors of coefficients below threshold in the case where the coef_ attribute of the estimator is of dimension 2. " />
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142 </section>
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143 </when>
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144 <when value="GenericUnivariateSelect">
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145 <expand macro="feature_selection_score_function" />
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146 <section name="options" title="Other Options" expanded="True">
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147 <param argument="mode" type="select" label="Feature selection mode">
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148 <option value="percentile">percentile</option>
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149 <option value="k_best">k_best</option>
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150 <option value="fpr">fpr</option>
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151 <option value="fdr">fdr</option>
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152 <option value="fwe">fwe</option>
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153 </param>
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154 <param argument="param" type="float" value="" optional="true" label="Parameter of the corresponding mode" help="float or int depending on the feature selection mode" />
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155 </section>
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156 </when>
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157 <when value="SelectPercentile">
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158 <expand macro="feature_selection_score_function" />
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159 <section name="options" title="Other Options" expanded="True">
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160 <param argument="percentile" type="integer" value="10" optional="True" label="Percent of features to keep" />
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161 </section>
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162 </when>
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163 <when value="SelectKBest">
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164 <expand macro="feature_selection_score_function" />
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165 <section name="options" title="Other Options" expanded="True">
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166 <param argument="k" type="integer" value="10" optional="True" label="Number of top features to select" help="No 'all' option is supported." />
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167 </section>
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168 </when>
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169 <when value="SelectFpr">
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170 <expand macro="feature_selection_score_function" />
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171 <section name="options" title="Other Options" expanded="True">
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172 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest p-value for features to be kept."/>
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173 </section>
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174 </when>
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175 <when value="SelectFdr">
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176 <expand macro="feature_selection_score_function" />
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177 <section name="options" title="Other Options" expanded="True">
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178 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest uncorrected p-value for features to keep."/>
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179 </section>
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180 </when>
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181 <when value="SelectFwe">
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182 <expand macro="feature_selection_score_function" />
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183 <section name="options" title="Other Options" expanded="True">
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184 <param argument="alpha" type="float" value="" optional="True" label="Alpha" help="The highest uncorrected p-value for features to keep."/>
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185 </section>
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186 </when>
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187 <when value="RFE">
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188 <expand macro="feature_selection_estimator" />
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189 <conditional name="extra_estimator">
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190 <expand macro="feature_selection_extra_estimator" />
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191 <expand macro="feature_selection_estimator_choices" />
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192 </conditional>
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193 <section name="options" title="Other Options" expanded="True">
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194 <param argument="n_features_to_select" type="integer" value="" optional="true" label="n_features_to_select" help="The number of features to select. If None, half of the features are selected." />
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195 <param argument="step" type="float" value="1" label="step" optional="true" help="Default = 1. " />
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196 <param argument="verbose" type="integer" value="0" label="verbose" help="Controls verbosity of output." />
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197 </section>
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198 </when>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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parents:
diff changeset
199 <when value="RFECV">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
200 <expand macro="feature_selection_estimator" />
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
201 <conditional name="extra_estimator">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
202 <expand macro="feature_selection_extra_estimator" />
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
203 <expand macro="feature_selection_estimator_choices" />
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
204 </conditional>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
205 <section name="options" title="Other Options" expanded="True">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
206 <param argument="step" type="float" value="1" label="step" optional="true" help="Default = 1. " />
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
207 <param argument="cv" type="integer" value="" optional="true" label="cv" help="Determines the cross-validation splitting strategy" />
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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208 <param argument="scoring" type="text" value="" optional="true" label="scoring" help="A string (see model evaluation documentation) or a scorer callable object / function with signature scorer(estimator, X, y)."/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
209 <param argument="verbose" type="integer" value="0" label="verbose" help="Controls verbosity of output." />
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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diff changeset
210 <param argument="n_jobs" type="integer" value="1" label="n_jobs" help="Number of cores to run in parallel while fitting across folds. Defaults to 1 core."/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
211 </section>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
212 </when>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
213 <when value="VarianceThreshold">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
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214 <section name="options" title="Options" expanded="True">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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215 <param argument="threshold" type="float" value="" optional="True" label="Threshold" help="Features with a training-set variance lower than this threshold will be removed."/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
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216 </section>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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parents:
diff changeset
217 </when>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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diff changeset
218 <!--when value="chi2">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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219 </when>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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parents:
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220 <when value="f_classif">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
221 </when>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
222 <when value="f_regression">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
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223 </when>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
224 <when value="mutual_info_classif">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
225 </when>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
226 <when value="mutual_info_regression">
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
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227 </when-->
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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228 </conditional>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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229 <expand macro="feature_selection_methods" />
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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230 <expand macro="sl_mixed_input"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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parents:
diff changeset
231 </inputs>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
232 <outputs>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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diff changeset
233 <data format="txt" name="outfile"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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parents:
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234 </outputs>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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parents:
diff changeset
235 <tests>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
236 <test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
237 <param name="selected_algorithm" value="SelectFromModel"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
238 <param name="has_estimator" value="no"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
239 <param name="new_estimator" value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
240 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
241 <param name="header1" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
242 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
243 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
244 <param name="col2" value="1"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
245 <param name="header2" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
246 <output name="outfile" file="feature_selection_result01"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
247 </test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
248 <test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
249 <param name="selected_algorithm" value="GenericUnivariateSelect"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
250 <param name="param" value="20"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
251 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
252 <param name="header1" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
253 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
254 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
255 <param name="col2" value="1"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
256 <param name="header2" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
257 <output name="outfile" file="feature_selection_result02"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
258 </test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
259 <test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
260 <param name="selected_algorithm" value="SelectPercentile"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
261 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
262 <param name="header1" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
263 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
264 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
265 <param name="col2" value="1"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
266 <param name="header2" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
267 <output name="outfile" file="feature_selection_result03"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
268 </test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
269 <test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
270 <param name="selected_algorithm" value="SelectKBest"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
271 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
272 <param name="header1" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
273 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
274 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
275 <param name="col2" value="1"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
276 <param name="header2" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
277 <output name="outfile" file="feature_selection_result04"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
278 </test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
279 <test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
280 <param name="selected_algorithm" value="SelectFpr"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
281 <param name="alpha" value="0.05"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
282 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
283 <param name="header1" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
284 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
285 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
286 <param name="col2" value="1"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
287 <param name="header2" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
288 <output name="outfile" file="feature_selection_result05"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
289 </test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
290 <test>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
291 <param name="selected_algorithm" value="SelectFdr"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
292 <param name="alpha" value="0.05"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
293 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
294 <param name="header1" value="True"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
bgruening
parents:
diff changeset
295 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
092199a095dd planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 7a31960686122d7e53054fef4996525f04ebd254
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296 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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297 <param name="col2" value="1"/>
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298 <param name="header2" value="True"/>
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299 <output name="outfile" file="feature_selection_result06"/>
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300 </test>
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301 <test>
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302 <param name="selected_algorithm" value="SelectFwe"/>
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303 <param name="alpha" value="0.05"/>
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304 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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305 <param name="header1" value="True"/>
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306 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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307 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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308 <param name="col2" value="1"/>
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309 <param name="header2" value="True"/>
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310 <output name="outfile" file="feature_selection_result07"/>
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311 </test>
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312 <test>
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313 <param name="selected_algorithm" value="RFE"/>
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314 <param name="has_estimator" value="no"/>
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315 <param name="new_estimator" value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)"/>
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316 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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317 <param name="header1" value="True"/>
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318 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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319 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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320 <param name="col2" value="1"/>
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321 <param name="header2" value="True"/>
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322 <output name="outfile" file="feature_selection_result08"/>
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323 </test>
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324 <test>
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325 <param name="selected_algorithm" value="RFECV"/>
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326 <param name="has_estimator" value="no"/>
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327 <param name="new_estimator" value="ensemble.RandomForestRegressor(n_estimators = 1000, random_state = 42)"/>
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328 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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329 <param name="header1" value="True"/>
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330 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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331 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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332 <param name="col2" value="1"/>
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333 <param name="header2" value="True"/>
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334 <output name="outfile" file="feature_selection_result09"/>
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335 </test>
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336 <test>
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337 <param name="selected_algorithm" value="VarianceThreshold"/>
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338 <param name="threshold" value="0.1"/>
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339 <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
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340 <param name="header1" value="True"/>
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341 <param name="col1" value="1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17"/>
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342 <param name="infile2" value="regression_y.tabular" ftype="tabular"/>
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343 <param name="col2" value="1"/>
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344 <param name="header2" value="True"/>
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345 <output name="outfile" file="feature_selection_result10"/>
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346 </test>
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347 </tests>
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348 <help>
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349 <![CDATA[
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350 **What it does**
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351 This tool provides several loss, score, and utility functions to measure classification performance. Some metrics might require probability estimates of the positive class, confidence values, or binary decisions values. This tool is based on
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352 sklearn.metrics package.
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353 For information about classification metric functions and their parameter settings please refer to `Scikit-learn classification metrics`_.
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354
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355 .. _`Scikit-learn classification metrics`: http://scikit-learn.org/stable/modules/model_evaluation.html#classification-metrics
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356 ]]>
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357 </help>
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358 <expand macro="sklearn_citation"/>
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359 </tool>