Branching on Prediction

cliftonarmscliftonarms Member Posts: 32 Contributor II
edited November 2018 in Help
I cannot seem to solve this design problem with the standard set of Rapidminer Processes and wonder if there is anyone more creative out there  ;)

The problem : I have a single binominal classification prediction example that I pass through Apply Model. I now need Rapidminer to select an external script depending on the prediction. I have tried the branch operator on the results from apply model then the external program process , but no success.

Anyone have any ideas - as I am a bit stuck.




Answers

  • Nils_WoehlerNils_Woehler Member Posts: 463 Maven
    Hi,

    you can use the branch operator for this purpose:

    <?xml version="1.0" encoding="UTF-8" standalone="no"?>
    <process version="5.3.006">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="5.3.006" expanded="true" name="Process">
        <process expanded="true">
          <operator activated="true" class="retrieve" compatibility="5.3.006" expanded="true" height="60" name="Retrieve Golf" width="90" x="112" y="120">
            <parameter key="repository_entry" value="//Samples/data/Golf"/>
          </operator>
          <operator activated="true" class="naive_bayes" compatibility="5.3.006" expanded="true" height="76" name="Naive Bayes" width="90" x="246" y="120"/>
          <operator activated="true" class="sample_stratified" compatibility="5.3.006" expanded="true" height="76" name="Sample (Stratified)" width="90" x="313" y="255">
            <parameter key="sample_size" value="1"/>
          </operator>
          <operator activated="true" class="apply_model" compatibility="5.3.006" expanded="true" height="76" name="Apply Model" width="90" x="514" y="210">
            <list key="application_parameters"/>
          </operator>
          <operator activated="true" class="branch" compatibility="5.3.006" expanded="true" height="76" name="Branch" width="90" x="715" y="210">
            <parameter key="condition_type" value="attribute_value_filter"/>
            <parameter key="condition_value" value="prediction(Play)=yes"/>
            <process expanded="true">
              <operator activated="true" class="print_to_console" compatibility="5.3.006" expanded="true" height="76" name="Print to Console" width="90" x="179" y="30">
                <parameter key="log_value" value="Yes!"/>
              </operator>
              <connect from_port="condition" to_op="Print to Console" to_port="through 1"/>
              <connect from_op="Print to Console" from_port="through 1" to_port="input 1"/>
              <portSpacing port="source_condition" spacing="0"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="sink_input 1" spacing="0"/>
              <portSpacing port="sink_input 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" class="print_to_console" compatibility="5.3.006" expanded="true" height="76" name="Print to Console (2)" width="90" x="179" y="30">
                <parameter key="log_value" value="No!"/>
              </operator>
              <connect from_port="condition" to_op="Print to Console (2)" to_port="through 1"/>
              <connect from_op="Print to Console (2)" from_port="through 1" to_port="input 1"/>
              <portSpacing port="source_condition" spacing="0"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="sink_input 1" spacing="0"/>
              <portSpacing port="sink_input 2" spacing="0"/>
            </process>
          </operator>
          <connect from_op="Retrieve Golf" from_port="output" to_op="Naive Bayes" to_port="training set"/>
          <connect from_op="Naive Bayes" from_port="model" to_op="Apply Model" to_port="model"/>
          <connect from_op="Naive Bayes" from_port="exampleSet" to_op="Sample (Stratified)" to_port="example set input"/>
          <connect from_op="Sample (Stratified)" from_port="example set output" to_op="Apply Model" to_port="unlabelled data"/>
          <connect from_op="Apply Model" from_port="labelled data" to_op="Branch" to_port="condition"/>
          <connect from_op="Branch" from_port="input 1" 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>
    Best,
    Nils
  • cliftonarmscliftonarms Member Posts: 32 Contributor II
    100% perfect - thank you

    I like Rapidminer more and more each day...Thanks team.
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