/**
* Indicates whether feature selection needs to be performed at all for this experiment.
*
* @return Wheter feature selection needs to be performed at all for this experiment
* @throws Exception
*/
public static boolean NeedToSelectFeatures() throws Exception {
for (AbstractDataProcessor processor :
Singletons.ProcessorVault.IndependentVariableDataProcessors)
for (FeatureSelectionAlgorithm fsAlgorithm :
Singletons.Config.GetFeatureSelectionAlgorithms(processor))
if (FeatureSelectionEvaluator.NeedToSelectFeatures(processor, fsAlgorithm)) return true;
return false;
}
/**
* Indicates how many different combinations of data processor, feature-selection algorithm, and
* classification algorithm there are in this experiment.
*
* @param includeNumFeaturesOptions Whether to count each number of features options as separate
* classification algorithm
* @return Number of unique combinations
* @throws Exception
*/
private static int GetNumberClassificationCombinations(boolean includeNumFeaturesOptions)
throws Exception {
int count = 0;
for (AbstractDataProcessor processor :
Singletons.ProcessorVault.IndependentVariableDataProcessors)
for (FeatureSelectionAlgorithm fsAlgorithm :
Singletons.Config.GetFeatureSelectionAlgorithms(processor))
for (ClassificationAlgorithm classificationAlgorithm :
Singletons.Config.GetMainClassificationAlgorithms())
count +=
(includeNumFeaturesOptions
? Singletons.Config.GetNumFeaturesOptions(processor, fsAlgorithm).size()
: 1);
return count;
}
