Mercurial > repos > bgruening > sklearn_nn_classifier

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author bgruening
date Wed, 09 Aug 2023 12:57:05 +0000
parents 1d3447c2203c
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1 <tool id="sklearn_nn_classifier" name="Nearest Neighbors Classification" version="@VERSION@" profile="@PROFILE@">
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2 <description></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 '$nnc_script' '$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="nnc_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.neighbors
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21 import pandas
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23 from galaxy_ml.model_persist import dump_model_to_h5, load_model_from_h5
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24 from galaxy_ml.utils import clean_params, get_X_y
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27 input_json_path = sys.argv[1]
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28 with open(input_json_path, "r") as param_handler:
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29 params = json.load(param_handler)
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31 #if $selected_tasks.selected_task == "load":
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33 classifier_object = load_model_from_h5('$infile_model')
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34 classifier_object = clean_params(classifier_object)
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36 header = 'infer' if params["selected_tasks"]["header"] else None
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37 data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=header, index_col=None, parse_dates=True, encoding=None)
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38 prediction = classifier_object.predict(data)
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39 prediction_df = pandas.DataFrame(prediction)
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40 res = pandas.concat([data, prediction_df], axis=1)
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41 res.to_csv(path_or_buf = "$outfile_predict", sep="\t", index=False)
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43 #else:
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45 X, y = get_X_y(params, "$selected_tasks.selected_algorithms.input_options.infile1" ,"$selected_tasks.selected_algorithms.input_options.infile2")
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47 selected_algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"]
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49 if selected_algorithm == "nneighbors":
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50 classifier = params["selected_tasks"]["selected_algorithms"]["sampling_methods"]["sampling_method"]
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51 sys.stdout.write(classifier)
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52 options = params["selected_tasks"]["selected_algorithms"]["sampling_methods"]["options"]
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53 sys.stdout.write(str(options))
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54 elif selected_algorithm == "ncentroid":
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55 options = params["selected_tasks"]["selected_algorithms"]["options"]
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56 classifier = "NearestCentroid"
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58 my_class = getattr(sklearn.neighbors, classifier)
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59 classifier_object = my_class(**options)
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60 classifier_object.fit(X, y)
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61
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62 dump_model_to_h5(classifier_object, '$outfile_fit')
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64 #end if
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66 ]]>
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67 </configfile>
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68 </configfiles>
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69 <inputs>
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70 <expand macro="sl_Conditional" model="h5mlm"> <!--Todo: add sparse to targets-->
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71 <param name="selected_algorithm" type="select" label="Classifier type">
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72 <option value="nneighbors">Nearest Neighbors</option>
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73 <option value="ncentroid">Nearest Centroid</option>
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74 </param>
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75 <when value="nneighbors">
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76 <expand macro="sl_mixed_input" />
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77 <conditional name="sampling_methods">
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78 <param name="sampling_method" type="select" label="Neighbor selection method">
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79 <option value="KNeighborsClassifier" selected="true">K-nearest neighbors</option>
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80 <option value="RadiusNeighborsClassifier">Radius-based</option>
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81 </param>
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82 <when value="KNeighborsClassifier">
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83 <expand macro="nn_advanced_options">
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84 <param argument="n_neighbors" type="integer" optional="true" value="5" label="Number of neighbors" help=" " />
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85 </expand>
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86 </when>
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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87 <when value="RadiusNeighborsClassifier">
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88 <expand macro="nn_advanced_options">
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89 <param argument="radius" type="float" optional="true" value="1.0" label="Radius" help="Range of parameter space to use by default for :meth ''radius_neighbors'' queries." />
0
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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90 </expand>
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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91 </when>
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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92 </conditional>
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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93 </when>
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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94 <when value="ncentroid">
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95 <expand macro="sl_mixed_input" />
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96 <section name="options" title="Advanced Options" expanded="False">
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97 <param argument="metric" type="text" optional="true" value="euclidean" label="Metric" help="The metric to use when calculating distance between instances in a feature array." />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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98 <param argument="shrink_threshold" type="float" optional="true" value="" label="Shrink threshold" help="Floating point number for shrinking centroids to remove features." />
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99 </section>
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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100 </when>
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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101 </expand>
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102 </inputs>
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103
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104 <expand macro="output" />
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105
b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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106 <tests>
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107 <test>
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108 <param name="infile1" value="train_set.tabular" ftype="tabular" />
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109 <param name="infile2" value="train_set.tabular" ftype="tabular" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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110 <param name="header1" value="True" />
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111 <param name="header2" value="True" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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112 <param name="col1" value="1,2,3,4" />
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113 <param name="col2" value="5" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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114 <param name="selected_task" value="train" />
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115 <param name="selected_algorithm" value="nneighbors" />
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116 <param name="sampling_method" value="KNeighborsClassifier" />
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117 <param name="algorithm" value="brute" />
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118 <output name="outfile_fit" file="nn_model01" compare="sim_size" delta="5" />
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119 </test>
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120 <test>
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121 <param name="infile1" value="train_set.tabular" ftype="tabular" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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122 <param name="infile2" value="train_set.tabular" ftype="tabular" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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123 <param name="header1" value="True" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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124 <param name="header2" value="True" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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125 <param name="col1" value="1,2,3,4" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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126 <param name="col2" value="5" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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127 <param name="selected_task" value="train" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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128 <param name="selected_algorithm" value="nneighbors" />
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129 <param name="sampling_method" value="RadiusNeighborsClassifier" />
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130 <param name="algorithm" value="brute" />
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131 <output name="outfile_fit" file="nn_model02" compare="sim_size" delta="5" />
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132 </test>
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133 <test>
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134 <param name="infile1" value="train_set.tabular" ftype="tabular" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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135 <param name="infile2" value="train_set.tabular" ftype="tabular" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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136 <param name="header1" value="True" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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137 <param name="header2" value="True" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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138 <param name="col1" value="1,2,3,4" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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139 <param name="col2" value="5" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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140 <param name="selected_task" value="train" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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141 <param name="selected_algorithm" value="ncentroid" />
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142 <output name="outfile_fit" file="nn_model03" compare="sim_size" delta="5" />
0
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143 </test>
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144 <test>
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145 <param name="infile_model" value="nn_model01" ftype="h5mlm" />
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146 <param name="infile_data" value="test_set.tabular" ftype="tabular" />
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147 <param name="header" value="True" />
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148 <param name="selected_task" value="load" />
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149 <output name="outfile_predict" file="nn_prediction_result01.tabular" />
0
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150 </test>
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151 <test>
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152 <param name="infile_model" value="nn_model02" ftype="h5mlm" />
21
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153 <param name="infile_data" value="test_set.tabular" ftype="tabular" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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154 <param name="header" value="True" />
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155 <param name="selected_task" value="load" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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156 <output name="outfile_predict" file="nn_prediction_result02.tabular" />
0
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157 </test>
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158 <test>
27
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159 <param name="infile_model" value="nn_model03" ftype="h5mlm" />
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160 <param name="infile_data" value="test_set.tabular" ftype="tabular" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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161 <param name="header" value="True" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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162 <param name="selected_task" value="load" />
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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163 <output name="outfile_predict" file="nn_prediction_result03.tabular" />
0
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164 </test>
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165 </tests>
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166 <help><![CDATA[
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167 **What it does**
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168 This module implements the k-nearest neighbors classification algorithms.
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169 For more information check http://scikit-learn.org/stable/modules/neighbors.html
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1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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170 ]]> </help>
1d3447c2203c "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
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171 <expand macro="sklearn_citation" />
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b7d0fc23bfe4 planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 8cbb681224f23fa95783514f949c97d6c2c60966
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172 </tool>