Optimize Parameters (Evolutionary)

bkruger

Hi,

Can anyone please direct me to a tutorial or example process of how to apply the results of optimize parameters (evolutionary) to a (new) test data set?

Thanks
BK

Skirzynski

Hey,

see the XML-code below

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.1.008">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="5.1.008" expanded="true" name="Process">
    <process expanded="true" height="533" width="748">
      <operator activated="true" class="retrieve" compatibility="5.1.008" expanded="true" height="60" name="Train" width="90" x="45" y="30">
        <parameter key="repository_entry" value="//Samples/data/Golf"/>
      </operator>
      <operator activated="true" class="multiply" compatibility="5.1.008" expanded="true" height="94" name="Multiply" width="90" x="179" y="30"/>
      <operator activated="true" class="optimize_parameters_evolutionary" compatibility="5.1.008" expanded="true" height="94" name="Optimize Parameters (Evolutionary)" width="90" x="380" y="30">
        <list key="parameters">
          <parameter key="tree-learner.minimal_gain" value="[0.0;500]"/>
        </list>
        <process expanded="true" height="533" width="774">
          <operator activated="true" class="decision_tree" compatibility="5.1.008" expanded="true" height="76" name="tree-learner" width="90" x="112" y="30">
            <parameter key="minimal_gain" value="110.22994197184146"/>
          </operator>
          <operator activated="true" class="apply_model" compatibility="5.1.008" expanded="true" height="76" name="Apply Model" width="90" x="246" y="30">
            <list key="application_parameters"/>
          </operator>
          <operator activated="true" class="performance" compatibility="5.1.008" expanded="true" height="76" name="Performance" width="90" x="447" y="30"/>
          <connect from_port="input 1" to_op="tree-learner" to_port="training set"/>
          <connect from_op="tree-learner" from_port="model" to_op="Apply Model" to_port="model"/>
          <connect from_op="tree-learner" from_port="exampleSet" 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="performance"/>
          <portSpacing port="source_input 1" spacing="0"/>
          <portSpacing port="source_input 2" spacing="0"/>
          <portSpacing port="sink_performance" spacing="0"/>
          <portSpacing port="sink_result 1" spacing="0"/>
        </process>
      </operator>
      <operator activated="true" class="set_parameters" compatibility="5.1.008" expanded="true" height="60" name="Set Parameters" width="90" x="514" y="120">
        <list key="name_map">
          <parameter key="tree-learner" value="optimal-tree-learner"/>
        </list>
      </operator>
      <operator activated="true" class="decision_tree" compatibility="5.1.008" expanded="true" height="76" name="optimal-tree-learner" width="90" x="380" y="210">
        <parameter key="minimal_gain" value="110.25191662265776"/>
      </operator>
      <connect from_op="Train" from_port="output" to_op="Multiply" to_port="input"/>
      <connect from_op="Multiply" from_port="output 1" to_op="Optimize Parameters (Evolutionary)" to_port="input 1"/>
      <connect from_op="Multiply" from_port="output 2" to_op="optimal-tree-learner" to_port="training set"/>
      <connect from_op="Optimize Parameters (Evolutionary)" from_port="parameter" to_op="Set Parameters" to_port="parameter set"/>
      <connect from_op="optimal-tree-learner" from_port="model" 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>