Mercurial > repos > bgruening > sklearn_generalized_linear

annotate generalized_linear.xml @ 10:bb91e46f8a9b draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 97c4f22cdcfa6cddeeffc7b102c418a7ff12a888
author bgruening
date Tue, 05 Jun 2018 06:43:16 -0400
parents 896ac1abafbf
children 20cf67b621df
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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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27 input_json_path = sys.argv[1]
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28 params = json.load(open(input_json_path, "r"))
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30 #if $selected_tasks.selected_task == "train":
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32 algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"]
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33 options = params["selected_tasks"]["selected_algorithms"]["options"]
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34
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35 #if $selected_tasks.selected_algorithms.input_options.selected_input=="tabular":
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36 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header1"] else None
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37 column_option = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_1"]["selected_column_selector_option"]
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38 if column_option == "by_index_number":
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39 c = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_1"]["col1"]
bb91e46f8a9b planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 97c4f22cdcfa6cddeeffc7b102c418a7ff12a888
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40 else:
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41 c = None
2
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42 X = read_columns(
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43 "$selected_tasks.selected_algorithms.input_options.infile1",
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44 c = c,
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45 c_option = column_option,
2
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46 sep='\t',
4
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47 header=header,
2
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48 parse_dates=True
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49 )
0
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50 #else:
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51 X = mmread(open("$selected_tasks.selected_algorithms.input_options.infile1", 'r'))
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52 #end if
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53
4
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54 header = 'infer' if params["selected_tasks"]["selected_algorithms"]["input_options"]["header2"] else None
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55 column_option = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_2"]["selected_column_selector_option2"]
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56 if column_option == "by_index_number":
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57 c = params["selected_tasks"]["selected_algorithms"]["input_options"]["column_selector_options_2"]["col2"]
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58 else:
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59 c = None
2
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60 y = read_columns(
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61 "$selected_tasks.selected_algorithms.input_options.infile2",
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62 c = c,
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63 c_option = column_option,
2
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64 sep='\t',
4
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65 header=header,
2
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66 parse_dates=True
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67 )
0
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68
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69 my_class = getattr(sklearn.linear_model, algorithm)
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70 estimator = my_class(**options)
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71 estimator.fit(X,y)
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72 pickle.dump(estimator,open("$outfile_fit", 'w+'), pickle.HIGHEST_PROTOCOL)
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73
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74 #else:
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75 classifier_object = pickle.load(open("$selected_tasks.infile_model", 'r'))
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76 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
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77 prediction = classifier_object.predict(data)
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78 prediction_df = pandas.DataFrame(prediction)
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79 res = pandas.concat([data, prediction_df], axis=1)
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80 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None)
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81 #end if
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82
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83 ]]>
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84 </configfile>
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85 </configfiles>
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86 <inputs>
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87 <expand macro="sl_Conditional" model="zip">
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88 <param name="selected_algorithm" type="select" label="Select a linear model:">
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89 <option value="SGDClassifier" selected="true">Stochastic Gradient Descent (SGD) classifier</option>
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90 <option value="SGDRegressor">Stochastic Gradient Descent (SGD) regressor</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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91 <option value="LinearRegression">Linear Regression model</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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92 <option value="RidgeClassifier">Ridge classifier</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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93 <option value="Ridge">Ridge regressor</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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94 <option value="LogisticRegression">Logistic Regression</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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95 <option value="LogisticRegressionCV">Logitic Regression with Cross Validation</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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96 <option value="Perceptron">Perceptron</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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97 </param>
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98 <when value="SGDClassifier">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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99 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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100 <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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101 <expand macro="loss">
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102 <option value="hinge" selected="true">hinge</option>
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103 <option value="log">log</option>
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104 <option value="modified_huber">modified huber</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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105 <option value="squared_hinge">squared hinge</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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106 <option value="perceptron">perceptron</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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107 </expand>
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108 <expand macro="penalty"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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109 <expand macro="alpha"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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110 <expand macro="l1_ratio"/>
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111 <expand macro="fit_intercept"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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112 <expand macro="n_iter" />
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113 <expand macro="shuffle"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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114 <expand macro="epsilon"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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115 <expand macro="learning_rate_s" selected1="true"/>
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116 <expand macro="eta0"/>
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117 <expand macro="power_t"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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118 <!--class_weight-->
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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119 <expand macro="warm_start" checked="false"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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120 <expand macro="random_state"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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121 <!--average-->
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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122 </section>
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123 </when>
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124 <when value="SGDRegressor">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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125 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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126 <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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127 <expand macro="loss" select="true"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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128 <expand macro="penalty"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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129 <expand macro="alpha"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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130 <expand macro="l1_ratio"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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131 <expand macro="fit_intercept"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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132 <expand macro="n_iter" />
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diff changeset
133 <expand macro="shuffle"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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134 <expand macro="epsilon"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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135 <expand macro="learning_rate_s" selected2="true"/>
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136 <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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137 <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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138 <expand macro="warm_start" checked="false"/>
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diff changeset
139 <expand macro="random_state"/>
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140 <!--average-->
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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141 </section>
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142 </when>
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143 <when value="LinearRegression">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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144 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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145 <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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146 <expand macro="fit_intercept"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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147 <expand macro="normalize"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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148 <expand macro="copy_X"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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149 </section>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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150 </when>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
151 <when value="RidgeClassifier">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
152 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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153 <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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154 <expand macro="ridge_params"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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155 </section>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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156 </when>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
157 <when value="Ridge">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
158 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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159 <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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diff changeset
160 <expand macro="ridge_params"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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161 </section>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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162 </when>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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163 <when value="LogisticRegression">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
164 <expand macro="sl_mixed_input"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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165 <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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166 <expand macro="penalty"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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167 <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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168 <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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169 <expand macro="C"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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170 <expand macro="fit_intercept"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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171 <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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172 <expand macro="warm_start" checked="false"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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173 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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174 <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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175 <option value="sag">sag</option>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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176 <option value="lbfgs">lbfgs</option>
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177 <option value="newton-cg">newton-cg</option>
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178 </param>
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179 <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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180 <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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181 <option value="ovr" selected="true">ovr</option>
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182 <option value="multinomial">multinomial</option>
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183 </param>
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184 <!--class_weight-->
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185 <expand macro="random_state"/>
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186 </section>
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187 </when>
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188 <when value="LogisticRegressionCV">
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189 <expand macro="sl_mixed_input"/>
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190 <section name="options" title="Advanced Options" expanded="False">
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191 <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. "/>
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192 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
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193 <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. "/>
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194 <expand macro="penalty"/>
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195 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/>
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196 <expand macro="fit_intercept"/>
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197 <expand macro="max_iter" default_value="100"/>
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198 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
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199 <option value="liblinear" selected="true">liblinear</option>
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200 <option value="sag">sag</option>
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201 <option value="lbfgs">lbfgs</option>
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202 <option value="newton-cg">newton-cg</option>
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203 </param>
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204 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/>
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205 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
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206 <option value="ovr" selected="true">ovr</option>
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207 <option value="multinomial">multinomial</option>
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208 </param>
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209 <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Average scores across all folds" help=" "/>
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210 <expand macro="random_state"/>
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211 <!--scoring=None>
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212 <class_weight=None-->
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213 </section>
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214 </when>
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215 <when value="Perceptron">
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216 <expand macro="sl_mixed_input"/>
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217 <section name="options" title="Advanced Options" expanded="False">
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218 <expand macro="penalty" default_value="none"/>
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219 <expand macro="alpha"/>
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220 <expand macro="fit_intercept"/>
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221 <expand macro="n_iter" />
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222 <expand macro="shuffle"/>
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223 <expand macro="eta0" default_value="1"/>
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224 <expand macro="warm_start" checked="false"/>
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225 <expand macro="random_state" default_value="0"/>
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226 <!--class_weight=None-->
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227 </section>
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228 </when>
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229 </expand>
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230 </inputs>
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231 <outputs>
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232 <data format="tabular" name="outfile_predict">
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233 <filter>selected_tasks['selected_task'] == 'load'</filter>
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234 </data>
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235 <data format="zip" name="outfile_fit">
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236 <filter>selected_tasks['selected_task'] == 'train'</filter>
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237 </data>
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238 </outputs>
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239 <tests>
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240 <test>
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241 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
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242 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
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243 <param name="col1" value="1,2,3,4,5"/>
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244 <param name="col2" value="6"/>
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245 <param name="selected_task" value="train"/>
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246 <param name="selected_algorithm" value="SGDRegressor"/>
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247 <param name="random_state" value="10"/>
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248 <output name="outfile_fit" file="glm_model01" compare="sim_size" delta="500"/>
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249 </test>
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250 <test>
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251 <param name="infile_model" value="glm_model01" ftype="zip"/>
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252 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
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253 <param name="selected_task" value="load"/>
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254 <output name="outfile_predict" file="glm_result01" compare="sim_size" delta="500"/>
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255 </test>
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256 <test>
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257 <param name="infile1" value="train.tabular" ftype="tabular"/>
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258 <param name="infile2" value="train.tabular" ftype="tabular"/>
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259 <param name="col1" value="1,2,3,4"/>
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260 <param name="col2" value="5"/>
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261 <param name="selected_task" value="train"/>
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262 <param name="selected_algorithm" value="SGDClassifier"/>
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263 <param name="random_state" value="10"/>
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264 <output name="outfile_fit" file="glm_model02" compare="sim_size" delta="500"/>
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265 </test>
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266 <test>
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267 <param name="infile_model" value="glm_model02" ftype="zip"/>
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268 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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269 <param name="selected_task" value="load"/>
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270 <output name="outfile_predict" file="glm_result02"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
271 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
272 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
273 <param name="infile1" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
274 <param name="infile2" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
275 <param name="col1" value="1,2,3,4"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
276 <param name="col2" value="5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
277 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
278 <param name="selected_algorithm" value="RidgeClassifier"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
279 <param name="random_state" value="10"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
280 <output name="outfile_fit" file="glm_model03" compare="sim_size" delta="500"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff changeset
281 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
282 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
283 <param name="infile_model" value="glm_model03" ftype="zip"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
284 <param name="infile_data" value="test.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
285 <param name="selected_task" value="load"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
286 <output name="outfile_predict" file="glm_result03"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff changeset
287 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
288 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
289 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
290 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
291 <param name="col1" value="1,2,3,4,5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
292 <param name="col2" value="6"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff changeset
293 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
294 <param name="selected_algorithm" value="LinearRegression"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
295 <param name="random_state" value="10"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
296 <output name="outfile_fit" file="glm_model04" compare="sim_size" delta="500"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
297 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
298 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
299 <param name="infile_model" value="glm_model04" ftype="zip"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
300 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
301 <param name="selected_task" value="load"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
302 <output name="outfile_predict" file="glm_result04" compare="sim_size"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff changeset
303 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
304 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
305 <param name="infile1" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
306 <param name="infile2" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
307 <param name="col1" value="1,2,3,4"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
308 <param name="col2" value="5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
309 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
310 <param name="selected_algorithm" value="LogisticRegression"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
311 <param name="random_state" value="10"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
312 <output name="outfile_fit" file="glm_model05" compare="sim_size" delta="500"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
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diff changeset
313 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
314 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
315 <param name="infile_model" value="glm_model05" ftype="zip"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
316 <param name="infile_data" value="test.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
317 <param name="selected_task" value="load"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
318 <output name="outfile_predict" file="glm_result05"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
319 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
320 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
321 <param name="infile1" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
322 <param name="infile2" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
323 <param name="col1" value="1,2,3,4"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
324 <param name="col2" value="5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
325 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
326 <param name="selected_algorithm" value="LogisticRegressionCV"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
327 <param name="random_state" value="10"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
328 <output name="outfile_fit" file="glm_model06" compare="sim_size" delta="500"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
329 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
330 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
331 <param name="infile_model" value="glm_model06" ftype="zip"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
332 <param name="infile_data" value="test.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
333 <param name="selected_task" value="load"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
334 <output name="outfile_predict" file="glm_result06"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
335 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
336 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
337 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
338 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
339 <param name="col1" value="1,2,3,4,5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
340 <param name="col2" value="6"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
341 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
342 <param name="selected_algorithm" value="Ridge"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
343 <param name="random_state" value="10"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
344 <output name="outfile_fit" file="glm_model07" compare="sim_size" delta="500"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
345 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
346 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
347 <param name="infile_model" value="glm_model07" ftype="zip"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
348 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
349 <param name="selected_task" value="load"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
350 <output name="outfile_predict" file="glm_result07" compare="sim_size"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
351 </test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
352 <test>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
353 <param name="infile1" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
354 <param name="infile2" value="train.tabular" ftype="tabular"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
355 <param name="col1" value="1,2,3,4"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
356 <param name="col2" value="5"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
diff changeset
357 <param name="selected_task" value="train"/>
6bc08bf6c6f3 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
bgruening
parents:
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358 <param name="selected_algorithm" value="LogisticRegressionCV"/>
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359 <param name="random_state" value="10"/>
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360 <output name="outfile_fit" file="glm_model08" compare="sim_size" delta="500"/>
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361 </test>
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362 <test>
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363 <param name="infile_model" value="glm_model08" ftype="zip"/>
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364 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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365 <param name="selected_task" value="load"/>
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366 <output name="outfile_predict" file="glm_result08"/>
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367 </test>
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368 </tests>
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369 <help><![CDATA[
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370 ***What it does***
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371 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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372
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373 .. _`Scikit-learn generalized linear models`: http://scikit-learn.org/stable/modules/linear_model.html
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374
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375 **1 - Methods**
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376 There are two groups of operations available:
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377
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378 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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379
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380 2 - Load a model and predict : An existing model predicts the class labels (or regression values) for a new dataset.
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381
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382 **2 - Trainig input**
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383 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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384
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385 **Sample tabular features dataset**
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386 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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387
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388 ::
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389
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390 4.01163365529 -6.10797684314 8.29829894763 1
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391 10.0788438916 1.59539821454 10.0684278289 0
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392 -5.17607775503 -0.878286135332 6.92941850665 2
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393 4.00975406235 -7.11847496542 9.3802423585 1
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394 4.61204065139 -5.71217537352 9.12509610964 1
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395
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396
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397 **Sample sparse features dataset**
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398 In this case you cannot specifiy a column range.
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399
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400 ::
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401
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402 4 1048577 8738
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403 1 271 0.020833
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404 1 1038 0.02461
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405 2 829017 0.016
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406 2 829437 0.012
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407 2 830752 0.025
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408 3 1047487 0.01
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409 3 1047980 0.02
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410 3 1048475 0.01
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411 4 608 0.016629
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412 4 1651 0.02519
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413 4 4053 0.04223
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414
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415
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416 **2 - Trainig output**
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417 The trained model is generated and output in the form of a binary file.
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418
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419
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420 **3 - Prediction input**
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421
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422 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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423
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424
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425 .. class:: warningmark
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426
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427 The number of feature columns must be the same in training and prediction datasets!
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428
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429
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430 **3 - Prediction output**
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431 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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432
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433 ]]></help>
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434 <expand macro="sklearn_citation"/>
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435 </tool>