DecisionTree.h

Go to the documentation of this file.

#ifndef GRT_DECISION_TREE_HEADER
#define GRT_DECISION_TREE_HEADER

#include "../../CoreModules/Classifier.h"
#include "../../CoreAlgorithms/Tree/Tree.h"
#include "DecisionTreeNode.h"
#include "DecisionTreeThresholdNode.h"
#include "DecisionTreeClusterNode.h"
#include "DecisionTreeTripleFeatureNode.h"

GRT_BEGIN_NAMESPACE

class GRT_API DecisionTree : public Classifier
{
public:
 DecisionTree(const DecisionTreeNode &decisionTreeNode = DecisionTreeClusterNode(),const UINT minNumSamplesPerNode=5,const UINT maxDepth=10,const bool removeFeaturesAtEachSplit = false,const Tree::TrainingMode trainingMode = Tree::TrainingMode::BEST_ITERATIVE_SPILT,const UINT numSplittingSteps=100,const bool useScaling=false );
 
 DecisionTree(const DecisionTree &rhs);
 
 virtual ~DecisionTree(void);
 
 DecisionTree &operator=(const DecisionTree &rhs);
 
 virtual bool deepCopyFrom(const Classifier *classifier) override;
 
 virtual bool train_(ClassificationData &trainingData) override;
 
 virtual bool predict_(VectorFloat &inputVector) override;
 
 virtual bool clear() override;
 
 virtual bool recomputeNullRejectionThresholds() override;
 
 virtual bool save( std::fstream &file ) const override;
 
 virtual bool load( std::fstream &file ) override;
 
 virtual bool getModel( std::ostream &stream ) const override;
 
 DecisionTreeNode* deepCopyTree() const;

 DecisionTreeNode* deepCopyDecisionTreeNode() const;
 
 const DecisionTreeNode* getTree() const;

 Tree::TrainingMode getTrainingMode() const;
 
 UINT getNumSplittingSteps() const;
 
 UINT getMinNumSamplesPerNode() const;
 
 UINT getMaxDepth() const;
 
 UINT getPredictedNodeID() const;
 
 bool getRemoveFeaturesAtEachSplit() const;
 
 bool setTrainingMode(const Tree::TrainingMode trainingMode);
 
 bool setNumSplittingSteps(const UINT numSplittingSteps);
 
 bool setMinNumSamplesPerNode(const UINT minNumSamplesPerNode);
 
 bool setMaxDepth(const UINT maxDepth);
 
 bool setRemoveFeaturesAtEachSplit(const bool removeFeaturesAtEachSplit);

 GRT_DEPRECATED_MSG( "setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt) is deprecated, use setRemoveFeaturesAtEachSplit(const bool removeFeaturesAtEachSplit) instead", bool setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt) );

 bool setDecisionTreeNode( const DecisionTreeNode &node );

 static std::string getId();
 
 //Tell the compiler we are using the base class train method to stop hidden virtual function warnings
 using MLBase::save;
 using MLBase::load;
 using MLBase::train_;
 using MLBase::predict_;
 using MLBase::print;
 
protected:
 bool loadLegacyModelFromFile_v1( std::fstream &file );
 bool loadLegacyModelFromFile_v2( std::fstream &file );
 bool loadLegacyModelFromFile_v3( std::fstream &file );
 
 bool trainTree( ClassificationData trainingData, const ClassificationData &trainingDataCopy, const ClassificationData &validationData, Vector< UINT > features );
 DecisionTreeNode* buildTree(ClassificationData &trainingData, DecisionTreeNode *parent, Vector< UINT > features, const Vector< UINT > &classLabels, UINT nodeID );
 Float getNodeDistance( const VectorFloat &x, const UINT nodeID );
 Float getNodeDistance( const VectorFloat &x, const VectorFloat &y );
 
 DecisionTreeNode* decisionTreeNode;
 std::map< UINT, VectorFloat > nodeClusters;
 VectorFloat classClusterMean;
 VectorFloat classClusterStdDev;

 DecisionTreeNode *tree; 
 UINT minNumSamplesPerNode;
 UINT maxDepth;
 UINT numSplittingSteps;
 bool removeFeaturesAtEachSplit;
 Tree::TrainingMode trainingMode;

private:
 static RegisterClassifierModule< DecisionTree > registerModule;
 static const std::string id;
};

GRT_END_NAMESPACE

#endif //GRT_DECISION_TREE_HEADER