annotate generalized_linear.xml @ 19:a259111a305a draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d00173591e4a783a4c1cb2664e4bb192ab5414f7
author bgruening
date Fri, 17 Aug 2018 12:30:04 -0400
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children 9b7d0655f70f
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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
19
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25 execfile("$__tool_directory__/utils.py")
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26
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27 input_json_path = sys.argv[1]
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28 with open(input_json_path, "r") as param_handler:
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29 params = json.load(param_handler)
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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" ,"$selected_tasks.selected_algorithms.input_options.infile2")
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34
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35 algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"]
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36 options = params["selected_tasks"]["selected_algorithms"]["options"]
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37
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38 my_class = getattr(sklearn.linear_model, algorithm)
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39 estimator = my_class(**options)
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40 estimator.fit(X,y)
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41 with open("$outfile_fit", 'wb') as out_handler:
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42 pickle.dump(estimator, out_handler, pickle.HIGHEST_PROTOCOL)
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43
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44 #else:
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45 with open("$selected_tasks.infile_model", 'rb') as model_handler:
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46 classifier_object = pickle.load(model_handler)
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47 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
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48 prediction = classifier_object.predict(data)
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49 prediction_df = pandas.DataFrame(prediction, columns=["predicted"])
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50 res = pandas.concat([data, prediction_df], axis=1)
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51 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None)
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52 #end if
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53
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54 ]]>
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55 </configfile>
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56 </configfiles>
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57 <inputs>
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58 <expand macro="sl_Conditional" model="zip">
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59 <param name="selected_algorithm" type="select" label="Select a linear model:">
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60 <option value="SGDClassifier" selected="true">Stochastic Gradient Descent (SGD) classifier</option>
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61 <option value="SGDRegressor">Stochastic Gradient Descent (SGD) regressor</option>
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62 <option value="LinearRegression">Linear Regression model</option>
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63 <option value="RidgeClassifier">Ridge classifier</option>
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64 <option value="Ridge">Ridge regressor</option>
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65 <option value="LogisticRegression">Logistic Regression</option>
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66 <option value="LogisticRegressionCV">Logitic Regression with Cross Validation</option>
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67 <option value="Perceptron">Perceptron</option>
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68 </param>
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69 <when value="SGDClassifier">
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70 <expand macro="sl_mixed_input"/>
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71 <section name="options" title="Advanced Options" expanded="False">
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72 <expand macro="loss">
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73 <option value="hinge" selected="true">hinge</option>
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74 <option value="log">log</option>
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75 <option value="modified_huber">modified huber</option>
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76 <option value="squared_hinge">squared hinge</option>
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77 <option value="perceptron">perceptron</option>
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78 </expand>
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79 <expand macro="penalty"/>
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80 <expand macro="alpha"/>
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81 <expand macro="l1_ratio"/>
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82 <expand macro="fit_intercept"/>
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83 <expand macro="n_iter" />
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84 <expand macro="shuffle"/>
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85 <expand macro="epsilon"/>
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86 <expand macro="learning_rate_s" selected1="true"/>
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87 <expand macro="eta0"/>
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88 <expand macro="power_t"/>
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89 <!--class_weight-->
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90 <expand macro="warm_start" checked="false"/>
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91 <expand macro="random_state"/>
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diff changeset
92 <!--average-->
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93 </section>
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94 </when>
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95 <when value="SGDRegressor">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
96 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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97 <section name="options" title="Advanced Options" expanded="False">
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diff changeset
98 <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
99 <expand macro="penalty"/>
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diff changeset
100 <expand macro="alpha"/>
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diff changeset
101 <expand macro="l1_ratio"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
102 <expand macro="fit_intercept"/>
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diff changeset
103 <expand macro="n_iter" />
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diff changeset
104 <expand macro="shuffle"/>
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diff changeset
105 <expand macro="epsilon"/>
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diff changeset
106 <expand macro="learning_rate_s" selected2="true"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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107 <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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108 <expand macro="power_t" default_value="0.25"/>
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109 <expand macro="warm_start" checked="false"/>
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110 <expand macro="random_state"/>
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diff changeset
111 <!--average-->
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112 </section>
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113 </when>
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114 <when value="LinearRegression">
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115 <expand macro="sl_mixed_input"/>
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116 <section name="options" title="Advanced Options" expanded="False">
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117 <expand macro="fit_intercept"/>
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118 <expand macro="normalize"/>
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parents:
diff changeset
119 <expand macro="copy_X"/>
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120 </section>
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121 </when>
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122 <when value="RidgeClassifier">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
123 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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124 <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
125 <expand macro="ridge_params"/>
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126 </section>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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127 </when>
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128 <when value="Ridge">
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diff changeset
129 <expand macro="sl_mixed_input"/>
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130 <section name="options" title="Advanced Options" expanded="False">
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diff changeset
131 <expand macro="ridge_params"/>
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132 </section>
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133 </when>
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134 <when value="LogisticRegression">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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135 <expand macro="sl_mixed_input"/>
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136 <section name="options" title="Advanced Options" expanded="False">
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diff changeset
137 <expand macro="penalty"/>
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138 <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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139 <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
140 <expand macro="C"/>
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141 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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142 <expand macro="max_iter" default_value="100"/>
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diff changeset
143 <expand macro="warm_start" checked="false"/>
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144 <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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145 <option value="liblinear" selected="true">liblinear</option>
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146 <option value="sag">sag</option>
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147 <option value="lbfgs">lbfgs</option>
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148 <option value="newton-cg">newton-cg</option>
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149 </param>
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diff changeset
150 <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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diff changeset
151 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
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152 <option value="ovr" selected="true">ovr</option>
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153 <option value="multinomial">multinomial</option>
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diff changeset
154 </param>
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diff changeset
155 <!--class_weight-->
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156 <expand macro="random_state"/>
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diff changeset
157 </section>
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158 </when>
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159 <when value="LogisticRegressionCV">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
160 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
161 <section name="options" title="Advanced Options" expanded="False">
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162 <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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163 <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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164 <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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diff changeset
165 <expand macro="penalty"/>
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diff changeset
166 <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
167 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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168 <expand macro="max_iter" default_value="100"/>
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diff changeset
169 <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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170 <option value="liblinear" selected="true">liblinear</option>
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171 <option value="sag">sag</option>
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172 <option value="lbfgs">lbfgs</option>
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173 <option value="newton-cg">newton-cg</option>
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174 </param>
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175 <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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176 <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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177 <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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178 <option value="multinomial">multinomial</option>
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179 </param>
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180 <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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181 <expand macro="random_state"/>
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182 <!--scoring=None>
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183 <class_weight=None-->
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184 </section>
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185 </when>
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186 <when value="Perceptron">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
187 <expand macro="sl_mixed_input"/>
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188 <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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189 <expand macro="penalty" default_value="none"/>
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diff changeset
190 <expand macro="alpha"/>
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191 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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192 <expand macro="n_iter" />
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193 <expand macro="shuffle"/>
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194 <expand macro="eta0" default_value="1"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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195 <expand macro="warm_start" checked="false"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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196 <expand macro="random_state" default_value="0"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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197 <!--class_weight=None-->
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198 </section>
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199 </when>
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200 </expand>
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201 </inputs>
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202 <outputs>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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203 <data format="tabular" name="outfile_predict">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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204 <filter>selected_tasks['selected_task'] == 'load'</filter>
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205 </data>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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206 <data format="zip" name="outfile_fit">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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207 <filter>selected_tasks['selected_task'] == 'train'</filter>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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208 </data>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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209 </outputs>
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210 <tests>
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211 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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212 <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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213 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
11
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diff changeset
214 <param name="selected_column_selector_option" value="all_but_by_index_number"/>
6cf4b82c72bc planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 64158f357e708f0b60d2669d92d614f7aee34c0e
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215 <param name="col1" value="6"/>
0
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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216 <param name="col2" value="6"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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217 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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218 <param name="selected_algorithm" value="SGDRegressor"/>
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219 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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220 <output name="outfile_fit" file="glm_model01" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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221 </test>
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222 <test>
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223 <param name="infile_model" value="glm_model01" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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224 <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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225 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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226 <output name="outfile_predict" file="glm_result01" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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227 </test>
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228 <test>
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229 <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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230 <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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231 <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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diff changeset
232 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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233 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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234 <param name="selected_algorithm" value="SGDClassifier"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
235 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
236 <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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diff changeset
237 </test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
238 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
239 <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
240 <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
241 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
242 <output name="outfile_predict" file="glm_result02"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
243 </test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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244 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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245 <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
246 <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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diff changeset
247 <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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diff changeset
248 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
249 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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250 <param name="selected_algorithm" value="RidgeClassifier"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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251 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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252 <output name="outfile_fit" file="glm_model03" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
253 </test>
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diff changeset
254 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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255 <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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diff changeset
256 <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
257 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
258 <output name="outfile_predict" file="glm_result03"/>
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259 </test>
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diff changeset
260 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
261 <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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diff changeset
262 <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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diff changeset
263 <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
264 <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
265 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
266 <param name="selected_algorithm" value="LinearRegression"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
267 <param name="random_state" value="10"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
268 <output name="outfile_fit" file="glm_model04" compare="sim_size" delta="500"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
269 </test>
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diff changeset
270 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
271 <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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diff changeset
272 <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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273 <param name="selected_task" value="load"/>
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274 <output name="outfile_predict" file="glm_result04" compare="sim_size"/>
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275 </test>
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276 <test>
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277 <param name="infile1" value="train.tabular" ftype="tabular"/>
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278 <param name="infile2" value="train.tabular" ftype="tabular"/>
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279 <param name="col1" value="1,2,3,4"/>
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280 <param name="col2" value="5"/>
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281 <param name="selected_task" value="train"/>
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282 <param name="selected_algorithm" value="LogisticRegression"/>
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283 <param name="random_state" value="10"/>
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284 <output name="outfile_fit" file="glm_model05" compare="sim_size" delta="500"/>
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285 </test>
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286 <test>
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287 <param name="infile_model" value="glm_model05" ftype="zip"/>
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288 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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289 <param name="selected_task" value="load"/>
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290 <output name="outfile_predict" file="glm_result05"/>
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291 </test>
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292 <test>
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293 <param name="infile1" value="train.tabular" ftype="tabular"/>
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294 <param name="infile2" value="train.tabular" ftype="tabular"/>
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295 <param name="col1" value="1,2,3,4"/>
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296 <param name="col2" value="5"/>
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297 <param name="selected_task" value="train"/>
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298 <param name="selected_algorithm" value="LogisticRegressionCV"/>
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299 <param name="random_state" value="10"/>
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300 <output name="outfile_fit" file="glm_model06" compare="sim_size" delta="500"/>
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301 </test>
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302 <test>
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303 <param name="infile_model" value="glm_model06" ftype="zip"/>
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304 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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305 <param name="selected_task" value="load"/>
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306 <output name="outfile_predict" file="glm_result06"/>
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307 </test>
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308 <test>
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309 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
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310 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
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311 <param name="col1" value="1,2,3,4,5"/>
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312 <param name="col2" value="6"/>
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313 <param name="selected_task" value="train"/>
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314 <param name="selected_algorithm" value="Ridge"/>
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315 <param name="random_state" value="10"/>
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316 <output name="outfile_fit" file="glm_model07" compare="sim_size" delta="500"/>
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317 </test>
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318 <test>
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319 <param name="infile_model" value="glm_model07" ftype="zip"/>
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320 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
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321 <param name="selected_task" value="load"/>
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322 <output name="outfile_predict" file="glm_result07" compare="sim_size"/>
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323 </test>
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324 <test>
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325 <param name="infile1" value="train.tabular" ftype="tabular"/>
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326 <param name="infile2" value="train.tabular" ftype="tabular"/>
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327 <param name="col1" value="1,2,3,4"/>
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328 <param name="col2" value="5"/>
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329 <param name="selected_task" value="train"/>
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330 <param name="selected_algorithm" value="LogisticRegressionCV"/>
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331 <param name="random_state" value="10"/>
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332 <output name="outfile_fit" file="glm_model08" compare="sim_size" delta="500"/>
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333 </test>
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334 <test>
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335 <param name="infile_model" value="glm_model08" ftype="zip"/>
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336 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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337 <param name="selected_task" value="load"/>
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338 <output name="outfile_predict" file="glm_result08"/>
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339 </test>
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340 </tests>
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341 <help><![CDATA[
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342 ***What it does***
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343 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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344
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345 .. _`Scikit-learn generalized linear models`: http://scikit-learn.org/stable/modules/linear_model.html
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346
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347 **1 - Methods**
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348 There are two groups of operations available:
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349
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350 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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351
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352 2 - Load a model and predict : An existing model predicts the class labels (or regression values) for a new dataset.
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353
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354 **2 - Trainig input**
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355 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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356
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357 **Sample tabular features dataset**
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358 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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359
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360 ::
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361
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362 4.01163365529 -6.10797684314 8.29829894763 1
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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363 10.0788438916 1.59539821454 10.0684278289 0
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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364 -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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365 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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366 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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367
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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368
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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369 **Sample sparse features dataset**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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370 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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371
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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372 ::
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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373
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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374 4 1048577 8738
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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375 1 271 0.020833
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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376 1 1038 0.02461
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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377 2 829017 0.016
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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378 2 829437 0.012
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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379 2 830752 0.025
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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380 3 1047487 0.01
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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381 3 1047980 0.02
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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382 3 1048475 0.01
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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383 4 608 0.016629
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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384 4 1651 0.02519
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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385 4 4053 0.04223
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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386
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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387
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388 **2 - Trainig output**
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389 The trained model is generated and output in the form of a binary file.
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390
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391
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392 **3 - Prediction input**
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393
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394 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.
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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395
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396
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397 .. class:: warningmark
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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398
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399 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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400
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401
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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402 **3 - Prediction output**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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403 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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404
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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405 ]]></help>
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406 <expand macro="sklearn_citation"/>
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407 </tool>