Hi,
I'm trying to log the results of a leave-one-out cross validation. This
is my (simplified) mode:
<operator name="Root" class="Process" expanded="yes">
<operator name="ExampleSource" class="ExampleSource">
<parameter key="attributes" value="../data/labor-negotiations.aml"/>
</operator>
<operator name="XValidation" class="XValidation" expanded="yes">
<parameter key="leave_one_out" value="true"/>
<parameter key="number_of_validations" value="5"/>
<operator name="DecisionTree" class="DecisionTree">
</operator>
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="ModelApplier" class="ModelApplier">
<list key="application_parameters">
</list>
</operator>
<operator name="ClassificationPerformance" class="ClassificationPerformance">
<parameter key="accuracy" value="true"/>
<parameter key="classification_error" value="true"/>
</operator>
<operator name="ProcessLog" class="ProcessLog">
<parameter key="filename" value="process.log"/>
<list key="log">
<parameter key="classification_error" value="operator.ClassificationPerformance.value.classification_error"/>
<parameter key="accurracy" value="operator.ClassificationPerformance.value.accuracy"/>
<parameter key="deviation" value="operator.XValidation.value.deviation"/>
</list>
<parameter key="persistent" value="true"/>
</operator>
</operator>
</operator>
</operator>
So, I'm trying to log the classification error and the accuracy of the ClassificationPerformance
operator as well as the deiation of the XValidation operator. However, the output is somehow unexpected:
# Generated by ProcessLog[com.rapidminer.operator.visualization.ProcessLogOperator]
# classification_error accurracy deviation
0.0 1.0 0.4175823272122516
0.0 1.0 0.4175823272122516
0.0 1.0 0.4175823272122516
...
I'm surprised why the first two values which vary between 0.0 and 1.0 do not
indicate the real classification error and accuracy measured for the validation
of a particular run. Also, I don't really understand why the deviation is always
the same. Should it not vary during the cross validation when different
accuracy values are collected?
If I'm doing something wrong, how can I correctly log the results of a
cross validation?
Regards,
Paul