Mercurial > repos > bgruening > sklearn_generalized_linear

annotate generalized_linear.xml @ 13:af9385cae623 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 14:29:40 -0400
parents 19c4cc592673
children 623c0ecb7102
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6bc08bf6c6f3 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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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" ,"$selected_tasks.selected_algorithms.input_options.infile2")
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34
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6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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35 algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"]
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36 options = params["selected_tasks"]["selected_algorithms"]["options"]
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37
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38 my_class = getattr(sklearn.linear_model, algorithm)
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39 estimator = my_class(**options)
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40 estimator.fit(X,y)
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41 pickle.dump(estimator,open("$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">
6bc08bf6c6f3 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">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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96 <expand macro="loss" select="true"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
97 <expand macro="penalty"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
98 <expand macro="alpha"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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99 <expand macro="l1_ratio"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
100 <expand macro="fit_intercept"/>
6bc08bf6c6f3 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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102 <expand macro="shuffle"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
103 <expand macro="epsilon"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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104 <expand macro="learning_rate_s" selected2="true"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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105 <expand macro="eta0" default_value="0.01"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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106 <expand macro="power_t" default_value="0.25"/>
6bc08bf6c6f3 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-->
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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110 </section>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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111 </when>
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112 <when value="LinearRegression">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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113 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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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117 <expand macro="copy_X"/>
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118 </section>
6bc08bf6c6f3 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">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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121 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 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">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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123 <expand macro="ridge_params"/>
6bc08bf6c6f3 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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126 <when value="Ridge">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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127 <expand macro="sl_mixed_input"/>
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128 <section name="options" title="Advanced Options" expanded="False">
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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">
6bc08bf6c6f3 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=" "/>
6bc08bf6c6f3 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. "/>
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138 <expand macro="C"/>
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139 <expand macro="fit_intercept"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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140 <expand macro="max_iter" default_value="100"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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=" ">
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143 <option value="liblinear" selected="true">liblinear</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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144 <option value="sag">sag</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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. "/>
6bc08bf6c6f3 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. ">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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150 <option value="ovr" selected="true">ovr</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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151 <option value="multinomial">multinomial</option>
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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">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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. "/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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161 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
6bc08bf6c6f3 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. "/>
6bc08bf6c6f3 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. "/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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165 <expand macro="fit_intercept"/>
6bc08bf6c6f3 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"/>
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167 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
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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. "/>
6bc08bf6c6f3 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. ">
6bc08bf6c6f3 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>
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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=" "/>
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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"/>
6bc08bf6c6f3 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"/>
20cf67b621df planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 64158f357e708f0b60d2669d92d614f7aee34c0e
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213 <param name="col1" value="6"/>
0
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214 <param name="col2" value="6"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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215 <param name="selected_task" value="train"/>
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216 <param name="selected_algorithm" value="SGDRegressor"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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222 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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223 <param name="selected_task" value="load"/>
6bc08bf6c6f3 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>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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227 <param name="infile1" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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228 <param name="infile2" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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229 <param name="col1" value="1,2,3,4"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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230 <param name="col2" value="5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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231 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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232 <param name="selected_algorithm" value="SGDClassifier"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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233 <param name="random_state" value="10"/>
6bc08bf6c6f3 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"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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235 </test>
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236 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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237 <param name="infile_model" value="glm_model02" ftype="zip"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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238 <param name="infile_data" value="test.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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239 <param name="selected_task" value="load"/>
6bc08bf6c6f3 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>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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243 <param name="infile1" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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244 <param name="infile2" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 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"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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246 <param name="col2" value="5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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247 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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248 <param name="selected_algorithm" value="RidgeClassifier"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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"/>
6bc08bf6c6f3 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"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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255 <param name="selected_task" value="load"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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256 <output name="outfile_predict" file="glm_result03"/>
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257 </test>
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diff changeset
258 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
259 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
260 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
261 <param name="col1" value="1,2,3,4,5"/>
6bc08bf6c6f3 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"/>
6bc08bf6c6f3 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"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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264 <param name="selected_algorithm" value="LinearRegression"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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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267 </test>
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268 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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269 <param name="infile_model" value="glm_model04" ftype="zip"/>
6bc08bf6c6f3 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"/>
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271 <param name="selected_task" value="load"/>
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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 ::
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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359
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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360 4.01163365529 -6.10797684314 8.29829894763 1
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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361 10.0788438916 1.59539821454 10.0684278289 0
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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362 -5.17607775503 -0.878286135332 6.92941850665 2
6bc08bf6c6f3 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
6bc08bf6c6f3 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
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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365
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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366
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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367 **Sample sparse features dataset**
6bc08bf6c6f3 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.
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369
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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370 ::
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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371
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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372 4 1048577 8738
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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373 1 271 0.020833
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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374 1 1038 0.02461
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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375 2 829017 0.016
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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376 2 829437 0.012
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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377 2 830752 0.025
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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378 3 1047487 0.01
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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379 3 1047980 0.02
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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380 3 1048475 0.01
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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381 4 608 0.016629
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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382 4 1651 0.02519
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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383 4 4053 0.04223
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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384
6bc08bf6c6f3 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
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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389
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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390 **3 - Prediction input**
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391
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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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
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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396
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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397 The number of feature columns must be the same in training and prediction datasets!
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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398
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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399
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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400 **3 - Prediction output**
6bc08bf6c6f3 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
6bc08bf6c6f3 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"/>
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405 </tool>