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annotate pre_process.xml @ 13:14f66545cc73 draft

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author bgruening
date Wed, 06 Jun 2018 17:39:09 -0400
parents 43075be4044b
children 928027486e78
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1 <tool id="sklearn_data_preprocess" name="Preprocess" version="@VERSION@">
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2 <description>raw feature vectors into standardized datasets</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>
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10 <![CDATA[
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11 python "$pre_processor_script" '$inputs'
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12 ]]>
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13 </command>
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14 <configfiles>
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15 <inputs name="inputs" />
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16 <configfile name="pre_processor_script">
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17 <![CDATA[
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18 import sys
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19 import json
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20 import pandas
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21 import pickle
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22 import numpy as np
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23 from scipy.io import mmread
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24 from scipy.io import mmwrite
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25 from sklearn import preprocessing
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26
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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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29
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30 #if $input_type.selected_input_type == "sparse":
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31 X = mmread(open("$infile", 'r'))
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32 #else:
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33 X = pandas.read_csv("$infile", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
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34 #end if
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35
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36 #if $input_type.pre_processors.infile_transform.ext == 'txt':
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37 y = mmread(open("$infile", 'r'))
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38 #else:
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39 y = pandas.read_csv("$infile", sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False )
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40 #end if
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41
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42 preprocessor = params["input_type"]["pre_processors"]["selected_pre_processor"]
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43 options = params["input_type"]["pre_processors"]["options"]
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44
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45 my_class = getattr(preprocessing, preprocessor)
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46 estimator = my_class(**options)
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47 estimator.fit(X)
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48 result = estimator.transform(y)
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49
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50 #if $input_type.pre_processors.infile_transform.ext == 'txt':
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51 mmwrite(open("$outfile_transform" , 'w+'), result)
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52 #else:
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53 res = pandas.DataFrame(result)
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54 res.to_csv(path_or_buf = "$outfile_transform", sep="\t", index=False, header=None)
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55 #end if
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56
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57 #if $save:
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58 pickle.dump(estimator,open("$outfile_fit", 'w+'), pickle.HIGHEST_PROTOCOL)
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59 #end if
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60 ]]>
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61 </configfile>
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62 </configfiles>
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63 <inputs>
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64 <conditional name="input_type">
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65 <param name="selected_input_type" type="select" label="Select the type of your input data:">
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66 <option value="tabular" selected="true">Tabular</option>
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67 <option value="sparse">Sparse</option>
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68 </param>
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69 <when value="tabular">
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70 <param name="infile" type="data" format="tabular" label="Select a tabular file you want to train your preprocessor on its data:"/>
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71 <conditional name="pre_processors">
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72 <expand macro="sparse_preprocessors">
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73 <option value="KernelCenterer">Kernel Centerer (Centers a kernel matrix)</option>
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74 <option value="MinMaxScaler">Minmax Scaler (Scales features to a range)</option>
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75 <option value="PolynomialFeatures">Polynomial Features (Generates polynomial and interaction features)</option>
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76 <option value="RobustScaler">Robust Scaler (Scales features using outlier-invariance statistics)</option>
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77 </expand>
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78 <expand macro="sparse_preprocessor_options">
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79 <when value="KernelCenterer">
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80 <expand macro="multitype_input"/>
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81 <section name="options" title="Advanced Options" expanded="False">
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82 </section>
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83 </when>
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84 <when value="MinMaxScaler">
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85 <expand macro="multitype_input"/>
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86 <section name="options" title="Advanced Options" expanded="False">
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87 <!--feature_range-->
2
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88 <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true"
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89 label="Use a copy of data for precomputing normalization" help=" "/>
0
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90 </section>
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91 </when>
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92 <when value="PolynomialFeatures">
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93 <expand macro="multitype_input"/>
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94 <section name="options" title="Advanced Options" expanded="False">
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95 <param argument="degree" type="integer" optional="true" value="2" label="The degree of the polynomial features " help=""/>
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96 <param argument="interaction_only" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="false" label="Produce interaction features only" help="(Features that are products of at most degree distinct input features) "/>
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97 <param argument="include_bias" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Include a bias column" help="Feature in which all polynomial powers are zero "/>
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98 </section>
2
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99 </when>
0
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100 <when value="RobustScaler">
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101 <expand macro="multitype_input"/>
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102 <section name="options" title="Advanced Options" expanded="False">
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103 <!--=True, =True, copy=True-->
2
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104 <param argument="with_centering" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true"
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105 label="Center the data before scaling" help=" "/>
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106 <param argument="with_scaling" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true"
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107 label="Scale the data to interquartile range" help=" "/>
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108 <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true"
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109 label="Use a copy of data for inplace scaling" help=" "/>
0
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110 </section>
2
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111 </when>
0
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112 </expand>
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113 </conditional>
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114 </when>
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115 <when value="sparse">
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116 <param name="infile" type="data" format="txt" label="Select a sparse representation you want to train your preprocessor on its data:"/>
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117 <conditional name="pre_processors">
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118 <expand macro="sparse_preprocessors"/>
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119 <expand macro="sparse_preprocessor_options"/>
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120 </conditional>
2
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121 </when>
0
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122 </conditional>
2
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123 <param name="save" type="boolean" truevalue="booltrue" falsevalue="boolflase" checked="false"
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124 label="Save the preprocessor"
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125 help="Saves the preprocessor after fitting to the data. The preprocessor can then be passed to other tools and used in later operations."/>
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126 </inputs>
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127 <outputs>
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128 <data format="tabular" name="outfile_transform" from_work_dir="./output"/>
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129 <data format="zip" name="outfile_fit">
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130 <filter>save</filter>
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131 </data>
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132 </outputs>
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133 <tests>
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134 <test>
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135 <param name="infile" value="train.tabular" ftype="tabular"/>
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136 <param name="infile_transform" value="train.tabular" ftype="tabular"/>
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137 <param name="selected_input_type" value="tabular"/>
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138 <param name="selected_pre_processor" value="KernelCenterer"/>
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139 <param name="save" value="true"/>
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140 <output name="outfile_transform" file="prp_result01" ftype="tabular"/>
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141 <output name="outfile_fit" file="prp_model01" ftype="zip" compare="sim_size" delta="500"/>
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142 </test>
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143 <test>
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144 <param name="infile" value="train.tabular" ftype="tabular"/>
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145 <param name="infile_transform" value="train.tabular" ftype="tabular"/>
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146 <param name="selected_input_type" value="tabular"/>
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147 <param name="selected_pre_processor" value="MinMaxScaler"/>
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148 <param name="save" value="true"/>
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149 <output name="outfile_transform" file="prp_result02" ftype="tabular"/>
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150 <output name="outfile_fit" file="prp_model02" ftype="zip" compare="sim_size" delta="500"/>
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151 </test>
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152 <test>
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153 <param name="infile" value="train.tabular" ftype="tabular"/>
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154 <param name="infile_transform" value="train.tabular" ftype="tabular"/>
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155 <param name="selected_input_type" value="tabular"/>
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156 <param name="selected_pre_processor" value="PolynomialFeatures"/>
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157 <param name="save" value="true"/>
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158 <output name="outfile_transform" file="prp_result03" ftype="tabular"/>
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159 <output name="outfile_fit" file="prp_model03" ftype="zip" compare="sim_size" delta="500"/>
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160 </test>
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161 <test>
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162 <param name="infile" value="train.tabular" ftype="tabular"/>
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163 <param name="infile_transform" value="train.tabular" ftype="tabular"/>
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164 <param name="selected_input_type" value="tabular"/>
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165 <param name="selected_pre_processor" value="RobustScaler"/>
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166 <param name="save" value="true"/>
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167 <output name="outfile_transform" file="prp_result04" ftype="tabular"/>
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168 <output name="outfile_fit" file="prp_model04" ftype="zip" compare="sim_size" delta="500"/>
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169 </test>
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170 <test>
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171 <param name="infile" value="csr_sparse2.mtx" ftype="txt"/>
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172 <param name="infile_transform" value="csr_sparse2.mtx" ftype="txt"/>
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173 <param name="selected_input_type" value="sparse"/>
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174 <param name="selected_pre_processor" value="Binarizer"/>
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175 <param name="save" value="true"/>
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176 <output name="outfile_transform" file="prp_result05" ftype="tabular"/>
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177 <output name="outfile_fit" file="prp_model05" ftype="zip" compare="sim_size" delta="500"/>
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178 </test>
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179 <test>
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180 <param name="infile" value="csr_sparse2.mtx" ftype="txt"/>
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181 <param name="infile_transform" value="csr_sparse2.mtx" ftype="txt"/>
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182 <param name="selected_input_type" value="sparse"/>
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183 <param name="selected_pre_processor" value="Imputer"/>
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184 <param name="save" value="true"/>
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185 <param name="axis" value="true"/>
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186 <output name="outfile_transform" file="prp_result06" ftype="tabular"/>
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187 <output name="outfile_fit" file="prp_model06" ftype="zip" compare="sim_size" delta="500"/>
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188 </test>
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189 <test>
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190 <param name="infile" value="train.tabular" ftype="tabular"/>
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191 <param name="infile_transform" value="train.tabular" ftype="tabular"/>
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192 <param name="selected_input_type" value="tabular"/>
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193 <param name="selected_pre_processor" value="StandardScaler"/>
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194 <param name="save" value="true"/>
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195 <output name="outfile_transform" file="prp_result07" ftype="tabular"/>
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196 <output name="outfile_fit" file="prp_model07" ftype="zip" compare="sim_size" delta="500"/>
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197 </test>
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198 <test>
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199 <param name="infile" value="csr_sparse2.mtx" ftype="txt"/>
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200 <param name="infile_transform" value="csr_sparse2.mtx" ftype="txt"/>
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201 <param name="selected_input_type" value="sparse"/>
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202 <param name="selected_pre_processor" value="MaxAbsScaler"/>
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203 <param name="save" value="true"/>
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204 <output name="outfile_transform" file="prp_result08" ftype="tabular"/>
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205 <output name="outfile_fit" file="prp_model08" ftype="zip" compare="sim_size" delta="500"/>
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206 </test>
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207 <test>
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208 <param name="infile" value="csr_sparse2.mtx" ftype="txt"/>
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209 <param name="infile_transform" value="csr_sparse2.mtx" ftype="txt"/>
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210 <param name="selected_input_type" value="sparse"/>
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211 <param name="selected_pre_processor" value="Normalizer"/>
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212 <param name="save" value="true"/>
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213 <output name="outfile_transform" file="prp_result09" ftype="tabular"/>
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214 <output name="outfile_fit" file="prp_model09" ftype="zip" compare="sim_size" delta="500"/>
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215 </test>
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216 </tests>
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217 <help>
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218 <![CDATA[
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219 **What it does**
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220
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221 This tool provides several transformer classes to change raw feature vectors into a representation that is more suitable for the downstream estimators. The library is provided by sklearn.preprocessing package.
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222
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223 For information about preprocessing classes and parameter settings please refer to `Scikit-learn preprocessing`_.
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224
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225 .. _`Scikit-learn preprocessing`: http://scikit-learn.org/stable/modules/preprocessing.html
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226 ]]>
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227 </help>
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228 <expand macro="sklearn_citation"/>
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229 </tool>