DecisionTreeTripleFeatureNode.h

Go to the documentation of this file.

#ifndef GRT_DECISION_TREE_TRIPLE_FEATURE_NODE_HEADER
#define GRT_DECISION_TREE_TRIPLE_FEATURE_NODE_HEADER

#include "DecisionTreeNode.h"
#include "../../ClusteringModules/KMeans/KMeans.h"

GRT_BEGIN_NAMESPACE
 
class GRT_API DecisionTreeTripleFeatureNode : public DecisionTreeNode{
public:
 DecisionTreeTripleFeatureNode();
 
 virtual ~DecisionTreeTripleFeatureNode();
 
 virtual bool predict_(VectorFloat &x) override;
 
 virtual bool clear() override;
 
 virtual bool print() const override;
 
 virtual bool getModel( std::ostream &stream ) const override;
 
 virtual Node* deepCopy() const override;
 
 UINT getFeatureIndexA() const;
 
 UINT getFeatureIndexB() const;
 
 UINT getFeatureIndexC() const;
 
 bool set(const UINT nodeSize,const UINT featureIndexA,const UINT featureIndexB,const UINT featureIndexC,const VectorFloat &classProbabilities);

 using DecisionTreeNode::predict_;
 
protected:
 
 virtual bool computeBestSplitBestIterativeSplit( const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError ) override;
 
 virtual bool computeBestSplitBestRandomSplit( const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError ) override;
 
 bool computeSplit( const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError );
 
 virtual bool saveParametersToFile( std::fstream &file ) const override;
 
 virtual bool loadParametersFromFile( std::fstream &file ) override;
 
 UINT featureIndexA;
 UINT featureIndexB;
 UINT featureIndexC;
 static RegisterNode< DecisionTreeTripleFeatureNode > registerModule;
};

GRT_END_NAMESPACE

#endif //GRT_DECISION_TREE_TRIPLE_FEATURE_NODE_HEADER