Mercurial > repos > bgruening > sklearn_generalized_linear

annotate generalized_linear.xml @ 13:cf635edf37d2 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 5d71c93a3dd804b1469852240a86021ab9130364
author bgruening
date Mon, 09 Jul 2018 14:33:39 -0400
parents 513405ebad8b
children 10a8543142fc
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32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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1 <tool id="sklearn_generalized_linear" name="Generalized linear models" version="@VERSION@">
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2 <description>for classification and regression</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><![CDATA[
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10 python "$glm_script" '$inputs'
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11 ]]>
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12 </command>
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13 <configfiles>
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14 <inputs name="inputs"/>
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15 <configfile name="glm_script">
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16 <![CDATA[
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17 import sys
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18 import json
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19 import numpy as np
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20 import sklearn.linear_model
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21 import pandas
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22 import pickle
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23 from scipy.io import mmread
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24
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25 @COLUMNS_FUNCTION@
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26 @GET_X_y_FUNCTION@
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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 #if $selected_tasks.selected_task == "train":
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32
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33 X, y = get_X_y(params, "$selected_tasks.selected_algorithms.input_options.infile1" ,"$selected_tasks.selected_algorithms.input_options.infile2")
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34
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35 algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"]
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36 options = params["selected_tasks"]["selected_algorithms"]["options"]
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38 my_class = getattr(sklearn.linear_model, algorithm)
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39 estimator = my_class(**options)
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40 estimator.fit(X,y)
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41 pickle.dump(estimator,open("$outfile_fit", 'w+'), pickle.HIGHEST_PROTOCOL)
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42
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43 #else:
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44 classifier_object = pickle.load(open("$selected_tasks.infile_model", 'r'))
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45 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
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46 prediction = classifier_object.predict(data)
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47 prediction_df = pandas.DataFrame(prediction)
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48 res = pandas.concat([data, prediction_df], axis=1)
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49 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None)
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50 #end if
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51
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52 ]]>
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53 </configfile>
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54 </configfiles>
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55 <inputs>
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56 <expand macro="sl_Conditional" model="zip">
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57 <param name="selected_algorithm" type="select" label="Select a linear model:">
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58 <option value="SGDClassifier" selected="true">Stochastic Gradient Descent (SGD) classifier</option>
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59 <option value="SGDRegressor">Stochastic Gradient Descent (SGD) regressor</option>
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60 <option value="LinearRegression">Linear Regression model</option>
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61 <option value="RidgeClassifier">Ridge classifier</option>
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62 <option value="Ridge">Ridge regressor</option>
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63 <option value="LogisticRegression">Logistic Regression</option>
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64 <option value="LogisticRegressionCV">Logitic Regression with Cross Validation</option>
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65 <option value="Perceptron">Perceptron</option>
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66 </param>
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67 <when value="SGDClassifier">
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68 <expand macro="sl_mixed_input"/>
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69 <section name="options" title="Advanced Options" expanded="False">
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70 <expand macro="loss">
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71 <option value="hinge" selected="true">hinge</option>
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72 <option value="log">log</option>
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73 <option value="modified_huber">modified huber</option>
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74 <option value="squared_hinge">squared hinge</option>
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75 <option value="perceptron">perceptron</option>
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76 </expand>
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77 <expand macro="penalty"/>
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78 <expand macro="alpha"/>
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79 <expand macro="l1_ratio"/>
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80 <expand macro="fit_intercept"/>
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81 <expand macro="n_iter" />
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82 <expand macro="shuffle"/>
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83 <expand macro="epsilon"/>
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84 <expand macro="learning_rate_s" selected1="true"/>
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85 <expand macro="eta0"/>
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86 <expand macro="power_t"/>
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87 <!--class_weight-->
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88 <expand macro="warm_start" checked="false"/>
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89 <expand macro="random_state"/>
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90 <!--average-->
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91 </section>
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92 </when>
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93 <when value="SGDRegressor">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
94 <expand macro="sl_mixed_input"/>
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95 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
96 <expand macro="loss" select="true"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
97 <expand macro="penalty"/>
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diff changeset
98 <expand macro="alpha"/>
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diff changeset
99 <expand macro="l1_ratio"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
100 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
101 <expand macro="n_iter" />
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diff changeset
102 <expand macro="shuffle"/>
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diff changeset
103 <expand macro="epsilon"/>
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104 <expand macro="learning_rate_s" selected2="true"/>
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diff changeset
105 <expand macro="eta0" default_value="0.01"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
106 <expand macro="power_t" default_value="0.25"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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107 <expand macro="warm_start" checked="false"/>
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108 <expand macro="random_state"/>
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109 <!--average-->
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110 </section>
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111 </when>
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112 <when value="LinearRegression">
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113 <expand macro="sl_mixed_input"/>
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114 <section name="options" title="Advanced Options" expanded="False">
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115 <expand macro="fit_intercept"/>
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116 <expand macro="normalize"/>
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diff changeset
117 <expand macro="copy_X"/>
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118 </section>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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119 </when>
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120 <when value="RidgeClassifier">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
121 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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122 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
123 <expand macro="ridge_params"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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124 </section>
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125 </when>
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parents:
diff changeset
126 <when value="Ridge">
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diff changeset
127 <expand macro="sl_mixed_input"/>
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128 <section name="options" title="Advanced Options" expanded="False">
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diff changeset
129 <expand macro="ridge_params"/>
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130 </section>
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131 </when>
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132 <when value="LogisticRegression">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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133 <expand macro="sl_mixed_input"/>
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134 <section name="options" title="Advanced Options" expanded="False">
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135 <expand macro="penalty"/>
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136 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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137 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
138 <expand macro="C"/>
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139 <expand macro="fit_intercept"/>
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140 <expand macro="max_iter" default_value="100"/>
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141 <expand macro="warm_start" checked="false"/>
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142 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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143 <option value="liblinear" selected="true">liblinear</option>
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144 <option value="sag">sag</option>
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145 <option value="lbfgs">lbfgs</option>
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146 <option value="newton-cg">newton-cg</option>
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147 </param>
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148 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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149 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
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150 <option value="ovr" selected="true">ovr</option>
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151 <option value="multinomial">multinomial</option>
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diff changeset
152 </param>
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153 <!--class_weight-->
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154 <expand macro="random_state"/>
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155 </section>
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156 </when>
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157 <when value="LogisticRegressionCV">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
158 <expand macro="sl_mixed_input"/>
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159 <section name="options" title="Advanced Options" expanded="False">
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160 <param argument="Cs" type="integer" value="10" label="Inverse of regularization strength" help="A grid of Cs values are chosen in a logarithmic scale between 1e-4 and 1e4. Like in support vector machines, smaller values specify stronger regularization. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
161 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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162 <param argument="cv" type="integer" optional="true" value="" label="Number of folds used in cross validation" help="If not set, the default cross-validation generator (Stratified K-Folds) is used. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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163 <expand macro="penalty"/>
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164 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
165 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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166 <expand macro="max_iter" default_value="100"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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167 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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168 <option value="liblinear" selected="true">liblinear</option>
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169 <option value="sag">sag</option>
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170 <option value="lbfgs">lbfgs</option>
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171 <option value="newton-cg">newton-cg</option>
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172 </param>
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173 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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174 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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175 <option value="ovr" selected="true">ovr</option>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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176 <option value="multinomial">multinomial</option>
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177 </param>
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178 <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Average scores across all folds" help=" "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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179 <expand macro="random_state"/>
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180 <!--scoring=None>
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181 <class_weight=None-->
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182 </section>
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183 </when>
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184 <when value="Perceptron">
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185 <expand macro="sl_mixed_input"/>
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186 <section name="options" title="Advanced Options" expanded="False">
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187 <expand macro="penalty" default_value="none"/>
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188 <expand macro="alpha"/>
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189 <expand macro="fit_intercept"/>
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190 <expand macro="n_iter" />
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191 <expand macro="shuffle"/>
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192 <expand macro="eta0" default_value="1"/>
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193 <expand macro="warm_start" checked="false"/>
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194 <expand macro="random_state" default_value="0"/>
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195 <!--class_weight=None-->
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196 </section>
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197 </when>
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198 </expand>
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199 </inputs>
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200 <outputs>
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201 <data format="tabular" name="outfile_predict">
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202 <filter>selected_tasks['selected_task'] == 'load'</filter>
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203 </data>
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204 <data format="zip" name="outfile_fit">
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205 <filter>selected_tasks['selected_task'] == 'train'</filter>
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206 </data>
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207 </outputs>
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208 <tests>
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209 <test>
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210 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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211 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
11
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212 <param name="selected_column_selector_option" value="all_but_by_index_number"/>
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213 <param name="col1" value="6"/>
0
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214 <param name="col2" value="6"/>
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215 <param name="selected_task" value="train"/>
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216 <param name="selected_algorithm" value="SGDRegressor"/>
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217 <param name="random_state" value="10"/>
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218 <output name="outfile_fit" file="glm_model01" compare="sim_size" delta="500"/>
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219 </test>
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220 <test>
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221 <param name="infile_model" value="glm_model01" ftype="zip"/>
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222 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
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223 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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224 <output name="outfile_predict" file="glm_result01" compare="sim_size" delta="500"/>
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225 </test>
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226 <test>
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227 <param name="infile1" value="train.tabular" ftype="tabular"/>
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228 <param name="infile2" value="train.tabular" ftype="tabular"/>
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229 <param name="col1" value="1,2,3,4"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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230 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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231 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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232 <param name="selected_algorithm" value="SGDClassifier"/>
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233 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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234 <output name="outfile_fit" file="glm_model02" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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235 </test>
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diff changeset
236 <test>
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237 <param name="infile_model" value="glm_model02" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
238 <param name="infile_data" value="test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
239 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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240 <output name="outfile_predict" file="glm_result02"/>
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241 </test>
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242 <test>
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243 <param name="infile1" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
244 <param name="infile2" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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245 <param name="col1" value="1,2,3,4"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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246 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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247 <param name="selected_task" value="train"/>
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248 <param name="selected_algorithm" value="RidgeClassifier"/>
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249 <param name="random_state" value="10"/>
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250 <output name="outfile_fit" file="glm_model03" compare="sim_size" delta="500"/>
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251 </test>
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252 <test>
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253 <param name="infile_model" value="glm_model03" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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254 <param name="infile_data" value="test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
255 <param name="selected_task" value="load"/>
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256 <output name="outfile_predict" file="glm_result03"/>
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257 </test>
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258 <test>
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259 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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260 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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261 <param name="col1" value="1,2,3,4,5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
262 <param name="col2" value="6"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
263 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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264 <param name="selected_algorithm" value="LinearRegression"/>
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265 <param name="random_state" value="10"/>
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266 <output name="outfile_fit" file="glm_model04" compare="sim_size" delta="500"/>
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diff changeset
267 </test>
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268 <test>
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269 <param name="infile_model" value="glm_model04" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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270 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
271 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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272 <output name="outfile_predict" file="glm_result04" compare="sim_size"/>
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273 </test>
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274 <test>
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275 <param name="infile1" value="train.tabular" ftype="tabular"/>
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276 <param name="infile2" value="train.tabular" ftype="tabular"/>
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277 <param name="col1" value="1,2,3,4"/>
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278 <param name="col2" value="5"/>
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279 <param name="selected_task" value="train"/>
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280 <param name="selected_algorithm" value="LogisticRegression"/>
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281 <param name="random_state" value="10"/>
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282 <output name="outfile_fit" file="glm_model05" compare="sim_size" delta="500"/>
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283 </test>
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284 <test>
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285 <param name="infile_model" value="glm_model05" ftype="zip"/>
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286 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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287 <param name="selected_task" value="load"/>
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288 <output name="outfile_predict" file="glm_result05"/>
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289 </test>
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290 <test>
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291 <param name="infile1" value="train.tabular" ftype="tabular"/>
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292 <param name="infile2" value="train.tabular" ftype="tabular"/>
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293 <param name="col1" value="1,2,3,4"/>
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294 <param name="col2" value="5"/>
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295 <param name="selected_task" value="train"/>
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296 <param name="selected_algorithm" value="LogisticRegressionCV"/>
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297 <param name="random_state" value="10"/>
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298 <output name="outfile_fit" file="glm_model06" compare="sim_size" delta="500"/>
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299 </test>
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300 <test>
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301 <param name="infile_model" value="glm_model06" ftype="zip"/>
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302 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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303 <param name="selected_task" value="load"/>
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304 <output name="outfile_predict" file="glm_result06"/>
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305 </test>
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306 <test>
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307 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
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308 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
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309 <param name="col1" value="1,2,3,4,5"/>
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310 <param name="col2" value="6"/>
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311 <param name="selected_task" value="train"/>
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312 <param name="selected_algorithm" value="Ridge"/>
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313 <param name="random_state" value="10"/>
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314 <output name="outfile_fit" file="glm_model07" compare="sim_size" delta="500"/>
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315 </test>
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316 <test>
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317 <param name="infile_model" value="glm_model07" ftype="zip"/>
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318 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
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319 <param name="selected_task" value="load"/>
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320 <output name="outfile_predict" file="glm_result07" compare="sim_size"/>
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321 </test>
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322 <test>
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323 <param name="infile1" value="train.tabular" ftype="tabular"/>
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324 <param name="infile2" value="train.tabular" ftype="tabular"/>
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325 <param name="col1" value="1,2,3,4"/>
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326 <param name="col2" value="5"/>
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327 <param name="selected_task" value="train"/>
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328 <param name="selected_algorithm" value="LogisticRegressionCV"/>
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329 <param name="random_state" value="10"/>
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330 <output name="outfile_fit" file="glm_model08" compare="sim_size" delta="500"/>
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331 </test>
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332 <test>
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333 <param name="infile_model" value="glm_model08" ftype="zip"/>
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334 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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335 <param name="selected_task" value="load"/>
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336 <output name="outfile_predict" file="glm_result08"/>
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337 </test>
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338 </tests>
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339 <help><![CDATA[
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340 ***What it does***
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341 This module implements a set of linear models for classification and regression such as: SGD classification and regression, Linear and Ridge regression and classification. This wrapper is using sklearn.linear_model module at its core. For information about linear models and their parameter settings please refer to `Scikit-learn generalized linear models`_.
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342
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343 .. _`Scikit-learn generalized linear models`: http://scikit-learn.org/stable/modules/linear_model.html
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344
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345 **1 - Methods**
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346 There are two groups of operations available:
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347
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348 1 - Train a model : A training set containing samples and their respective labels (or predicted values) are input. Based on the selected algorithm and options, an estimator object is fit to the data and is returned.
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349
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350 2 - Load a model and predict : An existing model predicts the class labels (or regression values) for a new dataset.
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351
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352 **2 - Trainig input**
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353 When you choose to train a model, you need a features dataset X and a labels set y. This tool expects tabular or sparse data for X and a single column for y (tabular). You can select a subset of columns in a tabular dataset as your features dataset or labels column. Below you find some examples:
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354
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355 **Sample tabular features dataset**
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356 The following training dataset contains 3 feature columns and a column containing class labels. You can simply select the first 3 columns as features and the last column as labels:
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357
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358 ::
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359
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360 4.01163365529 -6.10797684314 8.29829894763 1
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361 10.0788438916 1.59539821454 10.0684278289 0
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362 -5.17607775503 -0.878286135332 6.92941850665 2
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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363 4.00975406235 -7.11847496542 9.3802423585 1
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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364 4.61204065139 -5.71217537352 9.12509610964 1
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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365
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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366
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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367 **Sample sparse features dataset**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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368 In this case you cannot specifiy a column range.
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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369
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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370 ::
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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371
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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372 4 1048577 8738
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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373 1 271 0.020833
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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374 1 1038 0.02461
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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375 2 829017 0.016
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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376 2 829437 0.012
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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377 2 830752 0.025
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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378 3 1047487 0.01
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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379 3 1047980 0.02
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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380 3 1048475 0.01
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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381 4 608 0.016629
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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382 4 1651 0.02519
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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383 4 4053 0.04223
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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384
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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385
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386 **2 - Trainig output**
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387 The trained model is generated and output in the form of a binary file.
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388
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389
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390 **3 - Prediction input**
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391
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392 When you choose to load a model and do prediction, the tool expects an already trained estimator and a tabular dataset as input. The dataset contains new samples which you want to classify or predict regression values for.
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393
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394
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395 .. class:: warningmark
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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396
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397 The number of feature columns must be the same in training and prediction datasets!
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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398
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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399
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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400 **3 - Prediction output**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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401 The tool predicts the class labels for new samples and adds them as the last column to the prediction dataset. The new dataset then is output as a tabular file. The prediction output format should look like the training dataset.
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402
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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403 ]]></help>
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404 <expand macro="sklearn_citation"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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405 </tool>