RegressionTreeNode.h

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#ifndef GRT_REGRESSION_TREE_NODE_HEADER
#define GRT_REGRESSION_TREE_NODE_HEADER

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

GRT_BEGIN_NAMESPACE
 
class RegressionTreeNode : public Node{
public:
 RegressionTreeNode(){
 nodeType = "RegressionTreeNode";
 parent = NULL;
 leftChild = NULL;
 rightChild = NULL;
 clear();
 }
 
 virtual ~RegressionTreeNode(){
 clear();
 }
 
 virtual bool predict(const VectorFloat &x){
 if( x[ featureIndex ] >= threshold ) return true;
 return false;
 }
 
 virtual bool predict(const VectorFloat &x,VectorFloat &y){
 
 if( isLeafNode ){
 y = this->regressionData;
 return true;
 }
 
 if( leftChild == NULL && rightChild == NULL )
 return false;
 
 if( predict( x ) ){
 if( rightChild )
 return rightChild->predict( x, y );
 }else{
 if( leftChild )
 return leftChild->predict( x, y );
 }
 
 return false;
 }
 
 virtual bool clear(){
 
 //Call the base class clear function
 Node::clear();
 
 nodeSize = 0;
 featureIndex = 0;
 threshold = 0;
 regressionData.clear();
 
 return true;
 }
 
 virtual bool print() const{
 
 std::string tab = "";
 for(UINT i=0; i<depth; i++) tab += "\t";
 
 std::cout << tab << "depth: " << depth << " nodeSize: " << nodeSize << " featureIndex: " << featureIndex << " threshold " << threshold << " isLeafNode: " << isLeafNode << std::endl;
 std::cout << tab << "RegressionData: ";
 for(UINT i=0; i<regressionData.size(); i++){
 std::cout << regressionData[i] << "\t";
 }
 std::cout << std::endl;
 
 if( leftChild != NULL ){
 std::cout << tab << "LeftChild: " << std::endl;
 leftChild->print();
 }
 
 if( rightChild != NULL ){
 std::cout << tab << "RightChild: " << std::endl;
 rightChild->print();
 }
 
 return true;
 }
 
 virtual Node* deepCopyNode() const{
 
 RegressionTreeNode *node = new RegressionTreeNode;
 
 if( node == NULL ){
 return NULL;
 }
 
 //Copy this node into the node
 node->depth = this->depth;
 node->isLeafNode = this->isLeafNode;
 node->nodeSize = this->nodeSize;
 node->featureIndex = this->featureIndex;
 node->threshold = this->threshold;
 node->regressionData = this->regressionData;
 
 //Recursively deep copy the left child
 if( this->leftChild ){
 node->leftChild = this->leftChild->deepCopyNode();
 node->leftChild->setParent( node );
 }
 
 //Recursively deep copy the right child
 if( this->rightChild ){
 node->rightChild = this->rightChild->deepCopyNode();
 node->rightChild->setParent( node );
 }
 
 return dynamic_cast< Node* >( node );
 }
 
 RegressionTreeNode* deepCopyTree() const{
 RegressionTreeNode *node = dynamic_cast< RegressionTreeNode* >( deepCopyNode() );
 return node;
 }
 
 bool set(const UINT nodeSize,const UINT featureIndex,const Float threshold,const VectorFloat &regressionData){
 this->nodeSize = nodeSize;
 this->featureIndex = featureIndex;
 this->threshold = threshold;
 this->regressionData = regressionData;
 return true;
 }
 
protected:
 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 ClusterTreeNode parameters
 file << "NodeSize: " << nodeSize << std::endl;
 file << "FeatureIndex: " << featureIndex << std::endl;
 file << "Threshold: " << threshold << std::endl;
 file << "RegressionDataSize: " << regressionData.getSize() << std::endl;
 file << "RegressionData: ";
 for(unsigned int i=0; i<regressionData.getSize(); i++){
 file << regressionData[i] << " ";
 }
 file << std::endl;
 
 return true;
 }
 
 virtual bool loadParametersFromFile( std::fstream &file ){
 
 if(!file.is_open())
 {
 errorLog << "load(fstream &file) - File is not open!" << std::endl;
 return false;
 }
 
 std::string word;
 UINT regressionDataSize = 0;
 
 //Load the custom ClusterTreeNode 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 != "FeatureIndex:" ){
 errorLog << "loadParametersFromFile(fstream &file) - Failed to find FeatureIndex header!" << std::endl;
 return false;
 }
 file >> featureIndex;
 
 file >> word;
 if( word != "Threshold:" ){
 errorLog << "loadParametersFromFile(fstream &file) - Failed to find Threshold header!" << std::endl;
 return false;
 }
 file >> threshold;
 
 file >> word;
 if( word != "RegressionDataSize:" ){
 errorLog << "loadParametersFromFile(fstream &file) - Failed to find RegressionDataSize header!" << std::endl;
 return false;
 }
 file >> regressionDataSize;
 regressionData.resize(regressionDataSize);
 
 file >> word;
 if( word != "RegressionData:" ){
 errorLog << "loadParametersFromFile(fstream &file) - Failed to find RegressionData header!" << std::endl;
 return false;
 }
 for(unsigned int i=0; i<regressionData.getSize(); i++){
 file >> regressionData[i];
 }
 
 return true;
 }
 
 UINT nodeSize;
 UINT featureIndex;
 Float threshold;
 VectorFloat regressionData;
 
 static RegisterNode< RegressionTreeNode > registerModule;
};

GRT_END_NAMESPACE

#endif //GRT_REGRESSION_TREE_NODE_HEADER