LDA.h

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#ifndef GRT_LDA_HEADER
#define GRT_LDA_HEADER

#include "../../CoreModules/Classifier.h"
#include "../../Util/LUDecomposition.h"

GRT_BEGIN_NAMESPACE
 
class GRT_API LDAClassModel{
public:
 LDAClassModel(){
 classLabel = 0;
 priorProb = 0;
 }
 
 ~LDAClassModel(){
 
 }
 
 UINT getNumDimensions() const { return weights.getSize(); }
 
 UINT classLabel;
 Float priorProb;
 VectorDouble weights;
 
};
 
class GRT_API LDA : public Classifier
{
public:
 LDA(bool useScaling=false,bool useNullRejection=true,Float nullRejectionCoeff=10.0);
 
 virtual ~LDA(void);
 
 LDA &operator=(const LDA &rhs){
 if( this != &rhs ){
 //LDA variables
 this->models = rhs.models;
 
 //Classifier variables
 copyBaseVariables( (Classifier*)&rhs );
 }
 return *this;
 }
 
 //Override the base class methods
 virtual bool deepCopyFrom(const Classifier *classifier){
 if( classifier == NULL ) return false;
 
 if( this->getClassifierType() == classifier->getClassifierType() ){
 
 LDA *ptr = (LDA*)classifier;
 //Clone the LDA values 
 this->models = ptr->models;
 
 //Clone the classifier variables
 return copyBaseVariables( classifier );
 }
 return false;
 }
 
 virtual bool train(ClassificationData trainingData);
 
 virtual bool predict(VectorDouble inputVector);
 
 virtual bool saveModelToFile( std::fstream &file ) const;
 
 virtual bool loadModelFromFile( std::fstream &file );
 
 //Getters
 Vector< LDAClassModel > getModels(){ if( trained ){ return models; } return Vector< LDAClassModel >(); }
 
 //Setters

 //Tell the compiler we are using the base class train method to stop hidden virtual function warnings
 using MLBase::saveModelToFile;
 using MLBase::loadModelFromFile;

private:
 MatrixFloat computeBetweenClassScatterMatrix( ClassificationData &data );
 MatrixFloat computeWithinClassScatterMatrix( ClassificationData &data );
 
 Vector< LDAClassModel > models;
};

GRT_END_NAMESPACE

#endif //GRT_LDA_HEADER