public ISplittingResult SelectBestSplit(
IDataFrame baseData,
string dependentFeatureName,
ISplitQualityChecker splitQualityChecker,
IAlredyUsedAttributesInfo alreadyUsedAttributesInfo)
{
ISplittingResult bestSplit = null;
double bestSplitQuality = float.NegativeInfinity;
double initialEntropy = splitQualityChecker.GetInitialEntropy(baseData, dependentFeatureName);
foreach (var attributeToSplit in baseData.ColumnNames.Except(new[] { dependentFeatureName }))
{
if (baseData.GetColumnType(attributeToSplit).TypeIsNumeric())
{
// TODO: add checking for the already used attribtues
var bestNumericSplitPointAndQuality =
BinaryNumericBestSplitingPointSelector.FindBestSplitPoint(
baseData,
dependentFeatureName,
attributeToSplit,
splitQualityChecker,
BinaryNumericDataSplitter,
initialEntropy);
if (bestNumericSplitPointAndQuality.Item2 > bestSplitQuality)
{
bestSplitQuality = bestNumericSplitPointAndQuality.Item2;
bestSplit = bestNumericSplitPointAndQuality.Item1;
}
}
else
{
var bestSplitForAttribute = EvaluateCategoricalSplit(
baseData,
dependentFeatureName,
attributeToSplit,
bestSplitQuality,
initialEntropy,
splitQualityChecker,
alreadyUsedAttributesInfo);
if (bestSplitForAttribute.Item3 > bestSplitQuality)
{
bestSplit = BuildBestSplitObject(bestSplitForAttribute.Item2, bestSplitForAttribute.Item1);
bestSplitQuality = bestSplitForAttribute.Item3;
}
}
}
return(bestSplit);
}
public ISplittingResult SelectBestSplit(
IDataFrame baseData,
string dependentFeatureName,
ISplitQualityChecker splitQualityChecker,
IAlredyUsedAttributesInfo alreadyUsedAttributesInfo)
{
ISplittingResult bestSplit = null;
double bestSplitQuality = float.NegativeInfinity;
double initialEntropy = splitQualityChecker.GetInitialEntropy(baseData, dependentFeatureName);
foreach (var attributeToSplit in baseData.ColumnNames.Except(new[] { dependentFeatureName }))
{
if (baseData.GetColumnType(attributeToSplit).TypeIsNumeric())
{
// TODO: add checking for the already used attribtues
var bestNumericSplitPointAndQuality =
BinaryNumericBestSplitingPointSelector.FindBestSplitPoint(
baseData,
dependentFeatureName,
attributeToSplit,
splitQualityChecker,
BinaryNumericDataSplitter,
initialEntropy);
if (bestNumericSplitPointAndQuality.Item2 > bestSplitQuality)
{
bestSplitQuality = bestNumericSplitPointAndQuality.Item2;
bestSplit = bestNumericSplitPointAndQuality.Item1;
}
}
else
{
var bestSplitForAttribute = EvaluateCategoricalSplit(
baseData,
dependentFeatureName,
attributeToSplit,
bestSplitQuality,
initialEntropy,
splitQualityChecker,
alreadyUsedAttributesInfo);
if (bestSplitForAttribute.Item3 > bestSplitQuality)
{
bestSplit = BuildBestSplitObject(bestSplitForAttribute.Item2, bestSplitForAttribute.Item1);
bestSplitQuality = bestSplitForAttribute.Item3;
}
}
}
return bestSplit;
}
protected static bool ShouldStopRecusrsiveBuilding(IDataFrame dataFrame, string dependentFeatureName)
{
return !dataFrame.GetColumnType(dependentFeatureName).IsNumericType() && dataFrame.GetColumnVector<object>(dependentFeatureName).DataItems.Distinct().Count() == 1;
}
protected static bool ShouldStopRecusrsiveBuilding(IDataFrame dataFrame, string dependentFeatureName)
{
return(!dataFrame.GetColumnType(dependentFeatureName).IsNumericType() && dataFrame.GetColumnVector <object>(dependentFeatureName).DataItems.Distinct().Count() == 1);
}