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"Process failed one class svm error"

udaykumarudaykumar Member Posts: 6 Contributor I
edited June 2019 in Help
Hi

I am working with one class svm

my dataset looks like


a1                      a2                      a3                          a4                                label

date                binomial(text)  polynomial(text)  polynomial(text)                    error(one class label)

jan221990      os1                    mac                      networktimeout                error


I applied one class svm to the above data as follows but it is showing "process failed"

Please help me regarding this,


<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.000">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="5.3.000" expanded="true" name="Process">
    <process expanded="true" height="605" width="815">
      <operator activated="true" breakpoints="after" class="read_csv" compatibility="5.3.000" expanded="true" height="60" name="Read Train Data" width="90" x="45" y="75">
        <parameter key="csv_file" value="/home/hduser/Desktop/Datasets/Shuttle/sys_logSlot 3_new_oneclass.csv"/>
        <parameter key="first_row_as_names" value="false"/>
        <list key="annotations"/>
        <parameter key="encoding" value="UTF-8"/>
        <list key="data_set_meta_data_information">
          <parameter key="0" value="att1.false.polynominal.attribute"/>
          <parameter key="1" value="att2.false.binominal.attribute"/>
          <parameter key="2" value="att3.false.binominal.attribute"/>
          <parameter key="3" value="att4.true.binominal.attribute"/>
          <parameter key="4" value="att5.false.binominal.attribute"/>
          <parameter key="5" value="att6.false.polynominal.attribute"/>
          <parameter key="6" value="att7.false.polynominal.attribute"/>
          <parameter key="7" value="att8.false.binominal.attribute"/>
          <parameter key="8" value="att9.true.binominal.attribute"/>
          <parameter key="9" value="att10.true.binominal.attribute"/>
          <parameter key="10" value="att11.false.binominal.attribute"/>
          <parameter key="11" value="att12.false.polynominal.attribute"/>
          <parameter key="12" value="att13.false.polynominal.attribute"/>
          <parameter key="13" value="att14.false.binominal.attribute"/>
          <parameter key="14" value="att15.false.binominal.attribute"/>
          <parameter key="15" value="att16.true.binominal.attribute"/>
          <parameter key="16" value="att17.false.binominal.attribute"/>
          <parameter key="17" value="att18.false.polynominal.attribute"/>
          <parameter key="18" value="att19.false.polynominal.attribute"/>
          <parameter key="19" value="att20.false.binominal.attribute"/>
          <parameter key="20" value="att21.false.binominal.attribute"/>
          <parameter key="21" value="att22.true.binominal.attribute"/>
          <parameter key="22" value="att23.false.binominal.attribute"/>
          <parameter key="23" value="att24.false.polynominal.attribute"/>
          <parameter key="24" value="att25.false.polynominal.attribute"/>
          <parameter key="25" value="att26.false.binominal.attribute"/>
          <parameter key="26" value="att27.false.binominal.attribute"/>
          <parameter key="27" value="att28.true.binominal.attribute"/>
          <parameter key="28" value="att29.false.binominal.attribute"/>
          <parameter key="29" value="att30.false.polynominal.attribute"/>
          <parameter key="30" value="att31.true.binominal.label"/>
        </list>
      </operator>
      <operator activated="true" breakpoints="after" class="nominal_to_numerical" compatibility="5.3.000" expanded="true" height="94" name="Nominal to Numerical" width="90" x="179" y="30">
        <list key="comparison_groups"/>
      </operator>
      <operator activated="true" breakpoints="after" class="support_vector_machine_libsvm" compatibility="5.3.000" expanded="true" height="76" name="one-class SVM" width="90" x="380" y="75">
        <parameter key="svm_type" value="one-class"/>
        <parameter key="kernel_type" value="poly"/>
        <parameter key="nu" value="0.05"/>
        <list key="class_weights"/>
      </operator>
      <operator activated="true" breakpoints="after" class="read_csv" compatibility="5.3.000" expanded="true" height="60" name="Read CSV" width="90" x="45" y="210">
        <parameter key="csv_file" value="/home/hduser/Desktop/Datasets/Shuttle/sys_logSlot 3_new_oneclass_test.csv"/>
        <parameter key="first_row_as_names" value="false"/>
        <list key="annotations"/>
        <parameter key="encoding" value="UTF-8"/>
        <list key="data_set_meta_data_information">
          <parameter key="0" value="att1.false.polynominal.attribute"/>
          <parameter key="1" value="att2.false.binominal.attribute"/>
          <parameter key="2" value="att3.true.binominal.attribute"/>
          <parameter key="3" value="att4.false.binominal.attribute"/>
          <parameter key="4" value="att5.false.binominal.attribute"/>
          <parameter key="5" value="att6.false.polynominal.attribute"/>
          <parameter key="6" value="att7.false.polynominal.attribute"/>
          <parameter key="7" value="att8.false.binominal.attribute"/>
          <parameter key="8" value="att9.false.binominal.attribute"/>
          <parameter key="9" value="att10.true.binominal.attribute"/>
          <parameter key="10" value="att11.false.binominal.attribute"/>
          <parameter key="11" value="att12.false.polynominal.attribute"/>
          <parameter key="12" value="att13.false.polynominal.attribute"/>
          <parameter key="13" value="att14.false.binominal.attribute"/>
          <parameter key="14" value="att15.false.binominal.attribute"/>
          <parameter key="15" value="att16.true.binominal.attribute"/>
          <parameter key="16" value="att17.false.binominal.attribute"/>
          <parameter key="17" value="att18.false.polynominal.attribute"/>
          <parameter key="18" value="att19.false.polynominal.attribute"/>
          <parameter key="19" value="att20.false.binominal.attribute"/>
          <parameter key="20" value="att21.false.binominal.attribute"/>
          <parameter key="21" value="att22.true.binominal.attribute"/>
          <parameter key="22" value="att23.false.binominal.attribute"/>
          <parameter key="23" value="att24.true.polynominal.attribute"/>
          <parameter key="24" value="att25.false.polynominal.attribute"/>
          <parameter key="25" value="att26.false.binominal.attribute"/>
          <parameter key="26" value="att27.false.binominal.attribute"/>
          <parameter key="27" value="att28.true.binominal.attribute"/>
          <parameter key="28" value="att29.false.binominal.attribute"/>
          <parameter key="29" value="att30.false.polynominal.attribute"/>
          <parameter key="30" value="att31.true.binominal.label"/>
        </list>
      </operator>
      <operator activated="true" class="nominal_to_numerical" compatibility="5.3.000" expanded="true" height="94" name="Nominal to Numerical (2)" width="90" x="112" y="300">
        <list key="comparison_groups"/>
      </operator>
      <operator activated="true" breakpoints="after" class="apply_model" compatibility="5.3.000" expanded="true" height="76" name="Normalize (2)" width="90" x="246" y="390">
        <list key="application_parameters"/>
      </operator>
      <operator activated="true" breakpoints="after" class="apply_model" compatibility="5.3.000" expanded="true" height="76" name="Find Outliers" width="90" x="447" y="210">
        <list key="application_parameters"/>
      </operator>
      <operator activated="true" breakpoints="after" class="map" compatibility="5.3.000" expanded="true" height="76" name="Map" width="90" x="581" y="210">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="prediction(att31)"/>
        <list key="value_mappings">
          <parameter key="outside" value="outlier"/>
          <parameter key="inside" value="normal"/>
        </list>
      </operator>
      <operator activated="true" breakpoints="after" class="performance_classification" compatibility="5.3.000" expanded="true" height="76" name="Performance" width="90" x="514" y="345">
        <list key="class_weights"/>
      </operator>
      <connect from_op="Read Train Data" from_port="output" to_op="Nominal to Numerical" to_port="example set input"/>
      <connect from_op="Nominal to Numerical" from_port="example set output" to_op="one-class SVM" to_port="training set"/>
      <connect from_op="Nominal to Numerical" from_port="preprocessing model" to_op="Normalize (2)" to_port="model"/>
      <connect from_op="one-class SVM" from_port="model" to_op="Find Outliers" to_port="model"/>
      <connect from_op="Read CSV" from_port="output" to_op="Nominal to Numerical (2)" to_port="example set input"/>
      <connect from_op="Nominal to Numerical (2)" from_port="example set output" to_op="Normalize (2)" to_port="unlabelled data"/>
      <connect from_op="Normalize (2)" from_port="labelled data" to_op="Find Outliers" to_port="unlabelled data"/>
      <connect from_op="Find Outliers" from_port="labelled data" to_op="Map" to_port="example set input"/>
      <connect from_op="Map" from_port="example set output" to_op="Performance" to_port="labelled data"/>
      <connect from_op="Performance" from_port="performance" to_port="result 1"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
    </process>
  </operator>
</process>


The error is "Process failed"


Please help me regarding this as soon as possible



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Answers

  • mschmitzmschmitz Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 2,412  RM Data Scientist
    i can't reproduce this without the data.

    You might want to have a look at the anomaly extension. It has a capsuled one class svm you can use. Furthermore i would recommend to try a k-NN based LOF algorithm for your outliers as well.

    Cheers,

    Martin
    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
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