When I try to log the performance (rms error) of a model inside a feature selection process, it only works if I am using the single-threaded FeatureSelection node, not the parallel-processing-enabled FeatureSelectionParallel available in RM Enterprise.
In the two examples below, the ProcessLog in the former produces valid performance data, but the latter has all '?' in the performance column.
<operator name="Root" class="Process" expanded="yes">
<operator name="ExampleSetGenerator" class="ExampleSetGenerator">
<parameter key="target_function" value="non linear"/>
<parameter key="number_examples" value="1000"/>
</operator>
<operator name="AttributeConstruction" class="AttributeConstruction">
<list key="function_descriptions">
<parameter key="att_random1" value="rand()"/>
<parameter key="att_random2" value="rand()"/>
<parameter key="att_constant" value="0"/>
</list>
</operator>
<operator name="FeatureSelection" class="FeatureSelection" expanded="yes">
<parameter key="generations_without_improval" value="2"/>
<operator name="W-LWL" class="W-LWL">
<parameter key="keep_example_set" value="true"/>
<parameter key="K" value="5.0"/>
</operator>
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="ModelApplier" class="ModelApplier">
<list key="application_parameters">
</list>
</operator>
<operator name="RegressionPerformance" class="RegressionPerformance">
<parameter key="root_mean_squared_error" value="true"/>
</operator>
<operator name="ProcessLog" class="ProcessLog">
<list key="log">
<parameter key="generation" value="operator.FeatureSelection.value.generation"/>
<parameter key="feature_name" value="operator.FeatureSelection.value.feature_names"/>
<parameter key="performance" value="operator.RegressionPerformance.value.root_mean_squared_error"/>
</list>
</operator>
</operator>
</operator>
</operator>
<operator name="Root" class="Process" expanded="yes">
<operator name="ExampleSetGenerator" class="ExampleSetGenerator">
<parameter key="target_function" value="non linear"/>
<parameter key="number_examples" value="1000"/>
</operator>
<operator name="AttributeConstruction" class="AttributeConstruction">
<list key="function_descriptions">
<parameter key="att_random1" value="rand()"/>
<parameter key="att_random2" value="rand()"/>
<parameter key="att_constant" value="0"/>
</list>
</operator>
<operator name="FeatureSelectionParallel" class="FeatureSelectionParallel" expanded="yes">
<operator name="W-LWL" class="W-LWL">
<parameter key="keep_example_set" value="true"/>
<parameter key="K" value="5.0"/>
</operator>
<operator name="OperatorChain" class="OperatorChain" expanded="yes">
<operator name="ModelApplier" class="ModelApplier">
<list key="application_parameters">
</list>
</operator>
<operator name="RegressionPerformance" class="RegressionPerformance">
<parameter key="root_mean_squared_error" value="true"/>
</operator>
<operator name="ProcessLog" class="ProcessLog">
<list key="log">
<parameter key="generation" value="operator.FeatureSelectionParallel.value.generation"/>
<parameter key="feature_name" value="operator.FeatureSelectionParallel.value.feature_names"/>
<parameter key="performance" value="operator.RegressionPerformance.value.root_mean_squared_error"/>
</list>
</operator>
</operator>
</operator>
</operator>
