annotate generalized_linear.xml @ 30:67881a837f46 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit d6333e7294e67be5968a41f404b66699cad4ae53"
author bgruening
date Thu, 07 Nov 2019 05:36:10 -0500
parents 63417d0acc72
children a8c7b9fa426c
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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
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24 from scipy.io import mmread
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25 from galaxy_ml.utils import load_model, get_X_y
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28 input_json_path = sys.argv[1]
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29 with open(input_json_path, "r") as param_handler:
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30 params = json.load(param_handler)
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32 #if $selected_tasks.selected_task == "train":
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34 X, y = get_X_y(params, "$selected_tasks.selected_algorithms.input_options.infile1" ,"$selected_tasks.selected_algorithms.input_options.infile2")
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35
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36 algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"]
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37 options = params["selected_tasks"]["selected_algorithms"]["options"]
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38
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39 my_class = getattr(sklearn.linear_model, algorithm)
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40 estimator = my_class(**options)
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41 estimator.fit(X,y)
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42 with open("$outfile_fit", 'wb') as out_handler:
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43 pickle.dump(estimator, out_handler, pickle.HIGHEST_PROTOCOL)
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44
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45 #else:
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46 with open("$selected_tasks.infile_model", 'rb') as model_handler:
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47 classifier_object = load_model(model_handler)
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48 header = 'infer' if params["selected_tasks"]["header"] else None
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49 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False)
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50 prediction = classifier_object.predict(data)
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51 prediction_df = pandas.DataFrame(prediction, columns=["predicted"])
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52 res = pandas.concat([data, prediction_df], axis=1)
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53 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False, header=None)
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54 #end if
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55
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56 ]]>
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57 </configfile>
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58 </configfiles>
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59 <inputs>
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60 <expand macro="sl_Conditional" model="zip">
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61 <param name="selected_algorithm" type="select" label="Select a linear model:">
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62 <option value="SGDClassifier" selected="true">Stochastic Gradient Descent (SGD) classifier</option>
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63 <option value="SGDRegressor">Stochastic Gradient Descent (SGD) regressor</option>
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64 <option value="LinearRegression">Linear Regression model</option>
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65 <option value="RidgeClassifier">Ridge classifier</option>
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66 <option value="Ridge">Ridge regressor</option>
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67 <option value="LogisticRegression">Logistic Regression</option>
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68 <option value="LogisticRegressionCV">Logitic Regression with Cross Validation</option>
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69 <option value="Perceptron">Perceptron</option>
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70 </param>
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71 <when value="SGDClassifier">
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72 <expand macro="sl_mixed_input"/>
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73 <section name="options" title="Advanced Options" expanded="False">
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74 <expand macro="loss">
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75 <option value="hinge" selected="true">hinge</option>
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76 <option value="log">log</option>
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77 <option value="modified_huber">modified huber</option>
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78 <option value="squared_hinge">squared hinge</option>
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79 <option value="perceptron">perceptron</option>
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80 </expand>
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81 <expand macro="penalty"/>
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82 <expand macro="alpha"/>
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83 <expand macro="l1_ratio"/>
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84 <expand macro="fit_intercept"/>
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85 <expand macro="n_iter" />
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86 <expand macro="shuffle"/>
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87 <expand macro="epsilon"/>
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88 <expand macro="learning_rate_s" selected1="true"/>
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89 <expand macro="eta0"/>
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90 <expand macro="power_t"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
91 <!--class_weight-->
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parents:
diff changeset
92 <expand macro="warm_start" checked="false"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
93 <expand macro="random_state"/>
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parents:
diff changeset
94 <!--average-->
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
95 </section>
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96 </when>
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97 <when value="SGDRegressor">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
98 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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99 <section name="options" title="Advanced Options" expanded="False">
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diff changeset
100 <expand macro="loss" select="true"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
101 <expand macro="penalty"/>
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parents:
diff changeset
102 <expand macro="alpha"/>
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diff changeset
103 <expand macro="l1_ratio"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
104 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
105 <expand macro="n_iter" />
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
106 <expand macro="shuffle"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
107 <expand macro="epsilon"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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108 <expand macro="learning_rate_s" selected2="true"/>
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109 <expand macro="eta0" default_value="0.01"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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110 <expand macro="power_t" default_value="0.25"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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111 <expand macro="warm_start" checked="false"/>
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112 <expand macro="random_state"/>
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diff changeset
113 <!--average-->
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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114 </section>
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115 </when>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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116 <when value="LinearRegression">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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117 <expand macro="sl_mixed_input"/>
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118 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
119 <expand macro="fit_intercept"/>
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diff changeset
120 <expand macro="normalize"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
diff changeset
121 <expand macro="copy_X"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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122 </section>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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123 </when>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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124 <when value="RidgeClassifier">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
125 <expand macro="sl_mixed_input"/>
32a88b3bea94 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">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
127 <expand macro="ridge_params"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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128 </section>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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129 </when>
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diff changeset
130 <when value="Ridge">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
131 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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132 <section name="options" title="Advanced Options" expanded="False">
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diff changeset
133 <expand macro="ridge_params"/>
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134 </section>
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135 </when>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
136 <when value="LogisticRegression">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
137 <expand macro="sl_mixed_input"/>
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138 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
139 <expand macro="penalty"/>
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diff changeset
140 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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141 <expand macro="tol" default_value="0.0001" help_text="Tolerance for stopping criteria. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
142 <expand macro="C"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
143 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
144 <expand macro="max_iter" default_value="100"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
145 <expand macro="warm_start" checked="false"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
146 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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147 <option value="liblinear" selected="true">liblinear</option>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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148 <option value="sag">sag</option>
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149 <option value="lbfgs">lbfgs</option>
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150 <option value="newton-cg">newton-cg</option>
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151 </param>
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parents:
diff changeset
152 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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153 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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154 <option value="ovr" selected="true">ovr</option>
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155 <option value="multinomial">multinomial</option>
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diff changeset
156 </param>
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diff changeset
157 <!--class_weight-->
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diff changeset
158 <expand macro="random_state"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
159 </section>
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160 </when>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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parents:
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161 <when value="LogisticRegressionCV">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
162 <expand macro="sl_mixed_input"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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163 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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164 <param argument="Cs" type="integer" value="10" label="Inverse of regularization strength" help="A grid of Cs values are chosen in a logarithmic scale between 1e-4 and 1e4. Like in support vector machines, smaller values specify stronger regularization. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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165 <param argument="dual" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Use dual formulation" help=" "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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166 <param argument="cv" type="integer" optional="true" value="" label="Number of folds used in cross validation" help="If not set, the default cross-validation generator (Stratified K-Folds) is used. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
167 <expand macro="penalty"/>
32a88b3bea94 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. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
169 <expand macro="fit_intercept"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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170 <expand macro="max_iter" default_value="100"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
171 <param argument="solver" type="select" label="Optimization algorithm" help=" ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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172 <option value="liblinear" selected="true">liblinear</option>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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173 <option value="sag">sag</option>
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174 <option value="lbfgs">lbfgs</option>
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175 <option value="newton-cg">newton-cg</option>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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176 </param>
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177 <param argument="intercept_scaling" type="float" value="1" label="Intercept scaling factor" help="Useful only if solver is liblinear. "/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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178 <param argument="multi_class" type="select" label="Multiclass option" help="Works only for lbfgs solver. ">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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179 <option value="ovr" selected="true">ovr</option>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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180 <option value="multinomial">multinomial</option>
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181 </param>
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182 <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Average scores across all folds" help=" "/>
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183 <expand macro="random_state"/>
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184 <!--scoring=None>
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185 <class_weight=None-->
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186 </section>
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187 </when>
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188 <when value="Perceptron">
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189 <expand macro="sl_mixed_input"/>
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190 <section name="options" title="Advanced Options" expanded="False">
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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191 <expand macro="penalty" default_value="none"/>
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192 <expand macro="alpha"/>
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193 <expand macro="fit_intercept"/>
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194 <expand macro="n_iter" />
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195 <expand macro="shuffle"/>
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196 <expand macro="eta0" default_value="1"/>
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197 <expand macro="warm_start" checked="false"/>
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198 <expand macro="random_state" default_value="0"/>
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199 <!--class_weight=None-->
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200 </section>
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201 </when>
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202 </expand>
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203 </inputs>
21
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204 <expand macro="output"/>
0
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205 <tests>
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206 <test>
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207 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
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208 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
11
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209 <param name="selected_column_selector_option" value="all_but_by_index_number"/>
6cf4b82c72bc planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 64158f357e708f0b60d2669d92d614f7aee34c0e
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210 <param name="col1" value="6"/>
0
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211 <param name="col2" value="6"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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212 <param name="selected_task" value="train"/>
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213 <param name="selected_algorithm" value="SGDRegressor"/>
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214 <param name="random_state" value="10"/>
23
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215 <output name="outfile_fit" file="glm_model01" compare="sim_size" delta="5"/>
0
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216 </test>
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217 <test>
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218 <param name="infile_model" value="glm_model01" ftype="zip"/>
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219 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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220 <param name="selected_task" value="load"/>
23
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221 <output name="outfile_predict" file="glm_result01" lines_diff="4"/>
0
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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222 </test>
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223 <test>
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224 <param name="infile1" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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225 <param name="infile2" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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226 <param name="col1" value="1,2,3,4"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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227 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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228 <param name="selected_task" value="train"/>
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229 <param name="selected_algorithm" value="SGDClassifier"/>
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230 <param name="random_state" value="10"/>
23
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diff changeset
231 <output name="outfile_fit" file="glm_model02" compare="sim_size" delta="5"/>
0
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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232 </test>
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233 <test>
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234 <param name="infile_model" value="glm_model02" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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235 <param name="infile_data" value="test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
236 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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237 <output name="outfile_predict" file="glm_result02"/>
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238 </test>
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diff changeset
239 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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240 <param name="infile1" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
241 <param name="infile2" value="train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
242 <param name="col1" value="1,2,3,4"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
243 <param name="col2" value="5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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244 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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245 <param name="selected_algorithm" value="RidgeClassifier"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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246 <param name="random_state" value="10"/>
23
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diff changeset
247 <output name="outfile_fit" file="glm_model03" compare="sim_size" delta="5"/>
0
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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248 </test>
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249 <test>
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250 <param name="infile_model" value="glm_model03" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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251 <param name="infile_data" value="test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
252 <param name="selected_task" value="load"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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253 <output name="outfile_predict" file="glm_result03"/>
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254 </test>
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255 <test>
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diff changeset
256 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
257 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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258 <param name="col1" value="1,2,3,4,5"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
259 <param name="col2" value="6"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
260 <param name="selected_task" value="train"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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261 <param name="selected_algorithm" value="LinearRegression"/>
23
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diff changeset
262 <output name="outfile_fit" file="glm_model04" compare="sim_size" delta="5"/>
0
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
263 </test>
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diff changeset
264 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
265 <param name="infile_model" value="glm_model04" ftype="zip"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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diff changeset
266 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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267 <param name="selected_task" value="load"/>
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diff changeset
268 <output name="outfile_predict" file="glm_result04" lines_diff="8"/>
0
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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269 </test>
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270 <test>
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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271 <param name="infile1" value="train.tabular" ftype="tabular"/>
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272 <param name="infile2" value="train.tabular" ftype="tabular"/>
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273 <param name="col1" value="1,2,3,4"/>
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274 <param name="col2" value="5"/>
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275 <param name="selected_task" value="train"/>
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276 <param name="selected_algorithm" value="LogisticRegression"/>
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277 <param name="random_state" value="10"/>
23
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278 <output name="outfile_fit" file="glm_model05" compare="sim_size" delta="5"/>
0
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279 </test>
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280 <test>
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281 <param name="infile_model" value="glm_model05" ftype="zip"/>
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282 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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283 <param name="selected_task" value="load"/>
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284 <output name="outfile_predict" file="glm_result05"/>
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285 </test>
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286 <test>
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287 <param name="infile1" value="train.tabular" ftype="tabular"/>
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288 <param name="infile2" value="train.tabular" ftype="tabular"/>
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289 <param name="col1" value="1,2,3,4"/>
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290 <param name="col2" value="5"/>
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291 <param name="selected_task" value="train"/>
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292 <param name="selected_algorithm" value="LogisticRegressionCV"/>
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293 <param name="random_state" value="10"/>
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294 <output name="outfile_fit" file="glm_model06" compare="sim_size" delta="5"/>
0
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295 </test>
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296 <test>
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297 <param name="infile_model" value="glm_model06" ftype="zip"/>
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298 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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299 <param name="selected_task" value="load"/>
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300 <output name="outfile_predict" file="glm_result06"/>
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301 </test>
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302 <test>
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303 <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
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304 <param name="infile2" value="regression_train.tabular" ftype="tabular"/>
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305 <param name="col1" value="1,2,3,4,5"/>
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306 <param name="col2" value="6"/>
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307 <param name="selected_task" value="train"/>
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308 <param name="selected_algorithm" value="Ridge"/>
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309 <param name="random_state" value="10"/>
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310 <output name="outfile_fit" file="glm_model07" compare="sim_size" delta="5"/>
0
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311 </test>
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312 <test>
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313 <param name="infile_model" value="glm_model07" ftype="zip"/>
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314 <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
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315 <param name="selected_task" value="load"/>
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316 <output name="outfile_predict" file="glm_result07"/>
0
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317 </test>
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318 <test>
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319 <param name="infile1" value="train.tabular" ftype="tabular"/>
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320 <param name="infile2" value="train.tabular" ftype="tabular"/>
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321 <param name="col1" value="1,2,3,4"/>
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322 <param name="col2" value="5"/>
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323 <param name="selected_task" value="train"/>
22
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324 <param name="selected_algorithm" value="Perceptron"/>
0
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325 <param name="random_state" value="10"/>
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326 <output name="outfile_fit" file="glm_model08" compare="sim_size" delta="5"/>
0
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327 </test>
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328 <test>
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329 <param name="infile_model" value="glm_model08" ftype="zip"/>
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330 <param name="infile_data" value="test.tabular" ftype="tabular"/>
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331 <param name="selected_task" value="load"/>
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332 <output name="outfile_predict" file="glm_result08"/>
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333 </test>
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334 </tests>
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335 <help><![CDATA[
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336 ***What it does***
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337 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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338
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339 .. _`Scikit-learn generalized linear models`: http://scikit-learn.org/stable/modules/linear_model.html
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340
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341 **1 - Methods**
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342 There are two groups of operations available:
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343
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344 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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345
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346 2 - Load a model and predict : An existing model predicts the class labels (or regression values) for a new dataset.
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347
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348 **2 - Trainig input**
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349 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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350
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351 **Sample tabular features dataset**
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352 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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353
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354 ::
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355
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356 4.01163365529 -6.10797684314 8.29829894763 1
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357 10.0788438916 1.59539821454 10.0684278289 0
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358 -5.17607775503 -0.878286135332 6.92941850665 2
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359 4.00975406235 -7.11847496542 9.3802423585 1
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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360 4.61204065139 -5.71217537352 9.12509610964 1
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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361
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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362
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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363 **Sample sparse features dataset**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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364 In this case you cannot specifiy a column range.
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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365
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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366 ::
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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367
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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368 4 1048577 8738
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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369 1 271 0.020833
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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370 1 1038 0.02461
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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371 2 829017 0.016
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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372 2 829437 0.012
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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373 2 830752 0.025
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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374 3 1047487 0.01
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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375 3 1047980 0.02
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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376 3 1048475 0.01
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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377 4 608 0.016629
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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378 4 1651 0.02519
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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379 4 4053 0.04223
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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380
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381
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382 **2 - Trainig output**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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383 The trained model is generated and output in the form of a binary file.
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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384
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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385
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386 **3 - Prediction input**
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387
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388 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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389
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390
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391 .. class:: warningmark
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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392
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393 The number of feature columns must be the same in training and prediction datasets!
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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394
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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395
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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396 **3 - Prediction output**
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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397 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.
32a88b3bea94 planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit 0e582cf1f3134c777cce3aa57d71b80ed95e6ba9
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398
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399 ]]></help>
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400 <expand macro="sklearn_citation"/>
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401 </tool>