DecisionTreeThresholdNode.h

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#ifndef GRT_DECISION_TREE_THRESHOLD_NODE_HEADER
#define GRT_DECISION_TREE_THRESHOLD_NODE_HEADER

#include "DecisionTreeNode.h"

GRT_BEGIN_NAMESPACE
    
class GRT_API DecisionTreeThresholdNode : public DecisionTreeNode{
public:
    DecisionTreeThresholdNode();
    
    virtual ~DecisionTreeThresholdNode();
    
    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 getFeatureIndex() const;
    Float getThreshold() const;
    
    bool set(const UINT nodeSize,const UINT featureIndex,const Float threshold,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;
    
    virtual bool saveParametersToFile( std::fstream &file ) const override;
    
    virtual bool loadParametersFromFile( std::fstream &file ) override;
    
    UINT featureIndex;
    Float threshold;
    
    static RegisterNode< DecisionTreeThresholdNode > registerModule;
};

GRT_END_NAMESPACE

#endif //GRT_DECISION_TREE_THRESHOLD_NODE_HEADER