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Bug in Cross Validation Operator

Fred12Fred12 Member Posts: 344 Unicorn
edited November 2018 in Help

hi,

previously, I used Performance(Classification) in the old Validation (X-Validation) Operator.

 

cv.PNG

when I activated the cases for performance measures like weighted mean precision, margin, squared error etc. it was showed in the log operator outside the X-Validation.

 

However, with the new Cross Validation operator, the values of the Performance operator doesn't show anymore... its missing values instead "?"...

I think its a bug...

here is a XML example process with iris data to show the problem..

I could not find the old X-Validation anymore.. therefore the problem should be fixed soon please as I am constructing my wm_FScore out of the wm_Recall and wm_Precision

 

<?xml version="1.0" encoding="UTF-8"?><process version="7.4.000">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="7.4.000" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="retrieve" compatibility="7.4.000" expanded="true" height="68" name="Retrieve Iris" width="90" x="45" y="85">
        <parameter key="repository_entry" value="//Samples/data/Iris"/>
      </operator>
      <operator activated="true" class="x_validation" compatibility="7.4.000" expanded="true" height="124" name="Validation" width="90" x="447" y="85">
        <parameter key="number_of_validations" value="4"/>
        <parameter key="sampling_type" value="stratified sampling"/>
        <process expanded="true">
          <operator activated="true" class="support_vector_machine_libsvm" compatibility="7.4.000" expanded="true" height="82" name="SVM" width="90" x="112" y="34">
            <parameter key="gamma" value="0.007170375144641631"/>
            <parameter key="C" value="227500.0"/>
            <list key="class_weights"/>
          </operator>
          <connect from_port="training" to_op="SVM" to_port="training set"/>
          <connect from_op="SVM" from_port="model" to_port="model"/>
          <portSpacing port="source_training" spacing="0"/>
          <portSpacing port="sink_model" spacing="0"/>
          <portSpacing port="sink_through 1" spacing="0"/>
        </process>
        <process expanded="true">
          <operator activated="true" class="apply_model" compatibility="7.4.000" expanded="true" height="82" name="Apply Model" width="90" x="112" y="34">
            <list key="application_parameters"/>
          </operator>
          <operator activated="true" class="performance_classification" compatibility="7.4.000" expanded="true" height="82" name="Performance" width="90" x="313" y="34">
            <parameter key="kappa" value="true"/>
            <parameter key="weighted_mean_recall" value="true"/>
            <parameter key="weighted_mean_precision" value="true"/>
            <parameter key="correlation" value="true"/>
            <parameter key="squared_correlation" value="true"/>
            <parameter key="margin" value="true"/>
            <list key="class_weights"/>
          </operator>
          <connect from_port="model" to_op="Apply Model" to_port="model"/>
          <connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
          <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
          <connect from_op="Performance" from_port="performance" to_port="averagable 1"/>
          <portSpacing port="source_model" spacing="0"/>
          <portSpacing port="source_test set" spacing="0"/>
          <portSpacing port="source_through 1" spacing="0"/>
          <portSpacing port="sink_averagable 1" spacing="0"/>
          <portSpacing port="sink_averagable 2" spacing="0"/>
        </process>
      </operator>
      <operator activated="true" class="log" compatibility="7.4.000" expanded="true" height="82" name="Log" width="90" x="581" y="136">
        <list key="log">
          <parameter key="xvalperf" value="operator.Validation.value.performance"/>
          <parameter key="perfperf" value="operator.Performance.value.accuracy"/>
          <parameter key="perfkappa" value="operator.Performance.value.kappa"/>
          <parameter key="perfcorr" value="operator.Performance.value.correlation"/>
          <parameter key="perfwmprec" value="operator.Performance.value.weighted_mean_precision"/>
          <parameter key="perfwmrec" value="operator.Performance.value.weighted_mean_recall"/>
        </list>
      </operator>
      <operator activated="true" class="retrieve" compatibility="7.4.000" expanded="true" height="68" name="Retrieve Iris (2)" width="90" x="112" y="340">
        <parameter key="repository_entry" value="//Samples/data/Iris"/>
      </operator>
      <operator activated="true" class="concurrency:cross_validation" compatibility="7.4.000" expanded="true" height="145" name="Cross Validation" width="90" x="447" y="289">
        <process expanded="true">
          <operator activated="true" class="support_vector_machine_libsvm" compatibility="7.4.000" expanded="true" height="82" name="SVM (2)" width="90" x="45" y="34">
            <parameter key="gamma" value="0.007170375144641631"/>
            <parameter key="C" value="227500.0"/>
            <list key="class_weights"/>
          </operator>
          <connect from_port="training set" to_op="SVM (2)" to_port="training set"/>
          <connect from_op="SVM (2)" from_port="model" to_port="model"/>
          <portSpacing port="source_training set" spacing="0"/>
          <portSpacing port="sink_model" spacing="0"/>
          <portSpacing port="sink_through 1" spacing="0"/>
        </process>
        <process expanded="true">
          <operator activated="true" class="apply_model" compatibility="7.4.000" expanded="true" height="82" name="Apply Model (2)" width="90" x="112" y="34">
            <list key="application_parameters"/>
          </operator>
          <operator activated="true" class="performance_classification" compatibility="7.4.000" expanded="true" height="82" name="Performance (2)" width="90" x="313" y="34">
            <parameter key="kappa" value="true"/>
            <parameter key="weighted_mean_recall" value="true"/>
            <parameter key="weighted_mean_precision" value="true"/>
            <parameter key="correlation" value="true"/>
            <parameter key="squared_correlation" value="true"/>
            <parameter key="margin" value="true"/>
            <list key="class_weights"/>
          </operator>
          <connect from_port="model" to_op="Apply Model (2)" to_port="model"/>
          <connect from_port="test set" to_op="Apply Model (2)" to_port="unlabelled data"/>
          <connect from_op="Apply Model (2)" from_port="labelled data" to_op="Performance (2)" to_port="labelled data"/>
          <connect from_op="Performance (2)" from_port="performance" to_port="performance 1"/>
          <connect from_op="Performance (2)" from_port="example set" to_port="test set results"/>
          <portSpacing port="source_model" spacing="0"/>
          <portSpacing port="source_test set" spacing="0"/>
          <portSpacing port="source_through 1" spacing="0"/>
          <portSpacing port="sink_test set results" spacing="0"/>
          <portSpacing port="sink_performance 1" spacing="0"/>
          <portSpacing port="sink_performance 2" spacing="0"/>
        </process>
      </operator>
      <operator activated="true" class="log" compatibility="7.4.000" expanded="true" height="82" name="Log (2)" width="90" x="581" y="340">
        <list key="log">
          <parameter key="xvalperf" value="operator.Validation.value.performance"/>
          <parameter key="perfperf" value="operator.Performance.value.accuracy"/>
          <parameter key="perfkappa" value="operator.Performance (2).value.kappa"/>
          <parameter key="perfcorr" value="operator.Performance (2).value.correlation"/>
          <parameter key="perfwmprec" value="operator.Performance (2).value.weighted_mean_precision"/>
          <parameter key="perfwmrec" value="operator.Performance (2).value.weighted_mean_recall"/>
        </list>
      </operator>
      <connect from_op="Retrieve Iris" from_port="output" to_op="Validation" to_port="training"/>
      <connect from_op="Validation" from_port="averagable 1" to_op="Log" to_port="through 1"/>
      <connect from_op="Log" from_port="through 1" to_port="result 1"/>
      <connect from_op="Retrieve Iris (2)" from_port="output" to_op="Cross Validation" to_port="example set"/>
      <connect from_op="Cross Validation" from_port="performance 1" to_op="Log (2)" to_port="through 1"/>
      <connect from_op="Log (2)" from_port="through 1" to_port="result 2"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
      <portSpacing port="sink_result 3" spacing="0"/>
    </process>
  </operator>
</process>

 

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Best Answers

  • Thomas_OttThomas_Ott RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,761 Unicorn
    Solution Accepted

    Thanks @Fred12, something doesn't look quite right as you pointed out. I have passed this on internally. Thanks!

  • Telcontar120Telcontar120 RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 Unicorn
    Solution Accepted

    @Fred12 @Thomas_Ott Not a permanent solution, but a temporary workaround is to instead log the performance metric values  coming out of the Cross Validation operator directly.  You have the option of getting the first 3 in the log parameters.  

    See this xml version.

     

     

    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
  • Fred12Fred12 Member Posts: 344 Unicorn
    Solution Accepted

    thanks, that worked!

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