DecisionTreeNode.h

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#ifndef GRT_DECISION_TREE_NODE_HEADER
#define GRT_DECISION_TREE_NODE_HEADER

#include "../../CoreAlgorithms/Tree/Node.h"
#include "../../CoreAlgorithms/Tree/Tree.h"
#include "../../DataStructures/ClassificationData.h"

GRT_BEGIN_NAMESPACE
    
class DecisionTreeNode : public Node{
public:
    DecisionTreeNode();
    
    virtual ~DecisionTreeNode();
    
    virtual bool predict(const VectorFloat &x,VectorFloat &classLikelihoods);
    
    virtual bool computeBestSpilt( const UINT &trainingMode, const UINT &numSplittingSteps,const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError );

    virtual bool clear();
    
    virtual bool getModel( std::ostream &stream ) const;
    
    virtual Node* deepCopyNode() const;
    
    DecisionTreeNode* deepCopy() const;
    
    UINT getNodeSize() const;
    
    UINT getNumClasses() const;
    
    VectorFloat getClassProbabilities() const;
    
    bool setLeafNode( const UINT nodeSize, const VectorFloat &classProbabilities );
    
    bool setNodeSize(const UINT nodeSize);
    
    bool setClassProbabilities(const VectorFloat &classProbabilities);
    
    static UINT getClassLabelIndexValue(UINT classLabel,const Vector< UINT > &classLabels);
    
    using Node::predict;
    
protected:
    virtual bool computeBestSpiltBestIterativeSpilt( const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError ){
        
        errorLog << "computeBestSpiltBestIterativeSpilt(...) - Base class not overwritten!" << std::endl;
        
        return false;
    }
    
    virtual bool computeBestSpiltBestRandomSpilt( const UINT &numSplittingSteps, const ClassificationData &trainingData, const Vector< UINT > &features, const Vector< UINT > &classLabels, UINT &featureIndex, Float &minError ){
        
        errorLog << "computeBestSpiltBestRandomSpilt(...) - Base class not overwritten!" << std::endl;
        
        return false;
    }
    
    virtual bool saveParametersToFile( std::fstream &file ) const{
        
        if( !file.is_open() )
        {
            errorLog << "saveParametersToFile(fstream &file) - File is not open!" << std::endl;
            return false;
        }
        
        //Save the custom DecisionTreeNode parameters
        file << "NodeSize: " << nodeSize << std::endl;
        file << "NumClasses: " << classProbabilities.size() << std::endl;
        file << "ClassProbabilities: ";
        if( classProbabilities.size() > 0 ){
            for(UINT i=0; i<classProbabilities.size(); i++){
                file << classProbabilities[i];
                if( i < classProbabilities.size()-1 ) file << "\t";
                else file << std::endl;
            }
        }
        
        return true;
    }
    
    virtual bool loadParametersFromFile( std::fstream &file ){
        
        if( !file.is_open() )
        {
            errorLog << "loadParametersFromFile(fstream &file) - File is not open!" << std::endl;
            return false;
        }
        
        classProbabilities.clear();
        
        std::string word;
        UINT numClasses;
        
        //Load the custom DecisionTreeNode Parameters
        file >> word;
        if( word != "NodeSize:" ){
            errorLog << "loadParametersFromFile(fstream &file) - Failed to find NodeSize header!" << std::endl;
            return false;
        }
        file >> nodeSize;
        
        file >> word;
        if( word != "NumClasses:" ){
            errorLog << "loadParametersFromFile(fstream &file) - Failed to find NumClasses header!" << std::endl;
            return false;
        }
        file >> numClasses;
        if( numClasses > 0 )
            classProbabilities.resize( numClasses );
        
        file >> word;
        if( word != "ClassProbabilities:" ){
            errorLog << "loadParametersFromFile(fstream &file) - Failed to find ClassProbabilities header!" << std::endl;
            return false;
        }
        if( numClasses > 0 ){
            for(UINT i=0; i<numClasses; i++){
                file >> classProbabilities[i];
            }
        }
        
        return true;
    }
    
    UINT nodeSize;
    VectorFloat classProbabilities;
    
    static RegisterNode< DecisionTreeNode > registerModule;
};

GRT_END_NAMESPACE

#endif //GRT_DECISION_TREE_NODE_HEADER