Combining multiple performance vectors

wessel

Is is possible to combine multiple performance vector into a single averaged performance vector?

I use a single training set and multiple test sets, because I need both average accuracy and the standard deviation of the accuracy.

SebastianLoh

Hi wessel,

does this process answer your question?

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.0">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" expanded="true" name="Process">
    <process expanded="true" height="550" width="681">
      <operator activated="true" class="retrieve" expanded="true" height="60" name="test data" width="90" x="45" y="210">
        <parameter key="repository_entry" value="//Samples/data/Golf-Testset"/>
      </operator>
      <operator activated="true" class="retrieve" expanded="true" height="60" name="Retrieve" width="90" x="8" y="69">
        <parameter key="repository_entry" value="//Samples/data/Golf"/>
      </operator>
      <operator activated="true" class="decision_tree" expanded="true" height="76" name="Decision Tree" width="90" x="179" y="30"/>
      <operator activated="true" class="apply_model" expanded="true" height="76" name="Apply Model" width="90" x="179" y="165">
        <list key="application_parameters"/>
      </operator>
      <operator activated="true" class="performance_classification" expanded="true" height="76" name="Performance" width="90" x="246" y="300">
        <list key="class_weights"/>
      </operator>
      <operator activated="true" class="performance_classification" expanded="true" height="76" name="Performance (2)" width="90" x="258" y="426">
        <list key="class_weights"/>
      </operator>
      <operator activated="true" class="average" expanded="true" height="94" name="Average" width="90" x="581" y="255"/>
      <connect from_op="test data" from_port="output" to_op="Apply Model" to_port="unlabelled data"/>
      <connect from_op="Retrieve" from_port="output" to_op="Decision Tree" to_port="training set"/>
      <connect from_op="Decision Tree" from_port="model" to_op="Apply Model" to_port="model"/>
      <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
      <connect from_op="Apply Model" from_port="model" to_port="result 1"/>
      <connect from_op="Performance" from_port="performance" to_op="Average" to_port="averagable 1"/>
      <connect from_op="Performance" from_port="example set" to_op="Performance (2)" to_port="labelled data"/>
      <connect from_op="Performance (2)" from_port="performance" to_op="Average" to_port="averagable 2"/>
      <connect from_op="Average" from_port="average" 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>

Ciao Sebastian