/// <summary>
/// Determines whether the specified population is convergent.
/// </summary>
/// <param name="population">The population.</param>
/// <returns>
/// <c>true</c> if the specified population is convergent; otherwise, <c>false</c>.
/// </returns>
protected bool IsConvergent(Population population, Parameters parameters)
{
float avgEntropy = ShannonEntropy.GetGenesEntropy(population);
float convergence = parameters.ConvergenceLimit;
if (avgEntropy < convergence)
{
return(true);
}
return(false);
}
public BestSplitSelectorsTests()
{
ICategoricalImpurityMeasure<string> shannonEntropy = new ShannonEntropy<string>();
IBinaryDataSplitter binaryDataSplitter = new BinaryDiscreteDataSplitter();
binaryNumericBestSplitPointSelector = new ClassBreakpointsNumericSplitFinder();
binaryBestSplitSelector = new BinarySplitSelectorForCategoricalOutcome(binaryDataSplitter, binaryNumericDataSplitter, binaryNumericBestSplitPointSelector);
categoricalBinarySplitQualityChecker = new InformationGainCalculator<string>(shannonEntropy, shannonEntropy);
categoricalMultiValueSplitQualityChecker = new InformationGainCalculator<string>(shannonEntropy, shannonEntropy);
multiValueCategoricalDataSplitter = new MultiValueDiscreteDataSplitter();
multiValueBestSplitSelector = new MultiValueSplitSelectorForCategoricalOutcome(multiValueCategoricalDataSplitter, binaryNumericDataSplitter, binaryNumericBestSplitPointSelector);
dynamicProgrammingBestNumericSplitFinder = new DynamicProgrammingNumericSplitFinder();
}
public BestSplitSelectorsTests()
{
ICategoricalImpurityMeasure <string> shannonEntropy = new ShannonEntropy <string>();
IBinaryDataSplitter binaryDataSplitter = new BinaryDiscreteDataSplitter();
binaryNumericBestSplitPointSelector = new ClassBreakpointsNumericSplitFinder();
binaryBestSplitSelector = new BinarySplitSelectorForCategoricalOutcome(binaryDataSplitter, binaryNumericDataSplitter, binaryNumericBestSplitPointSelector);
categoricalBinarySplitQualityChecker = new InformationGainCalculator <string>(shannonEntropy, shannonEntropy);
categoricalMultiValueSplitQualityChecker = new InformationGainCalculator <string>(shannonEntropy, shannonEntropy);
multiValueCategoricalDataSplitter = new MultiValueDiscreteDataSplitter();
multiValueBestSplitSelector = new MultiValueSplitSelectorForCategoricalOutcome(multiValueCategoricalDataSplitter, binaryNumericDataSplitter, binaryNumericBestSplitPointSelector);
dynamicProgrammingBestNumericSplitFinder = new DynamicProgrammingNumericSplitFinder();
}
