GMM.h

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#ifndef GRT_GMM_HEADER
#define GRT_GMM_HEADER

#include "../../CoreModules/Classifier.h"
#include "../../ClusteringModules/GaussianMixtureModels/GaussianMixtureModels.h"
#include "MixtureModel.h"

#define GMM_MIN_SCALE_VALUE 0.0001
#define GMM_MAX_SCALE_VALUE 1.0

GRT_BEGIN_NAMESPACE

class GRT_API GMM : public Classifier
{
public:
 GMM(UINT numMixtureModels = 2,bool useScaling=false,bool useNullRejection=false,Float nullRejectionCoeff=1.0,UINT maxIter=100,Float minChange=1.0e-5);
 
 GMM(const GMM &rhs);
 
 virtual ~GMM(void);
 
 GMM &operator=(const GMM &rhs);
 
 virtual bool deepCopyFrom(const Classifier *classifier);
 
 virtual bool train_(ClassificationData &trainingData);
 
 virtual bool predict_(VectorFloat &inputVector);
 
 virtual bool clear();
 
 virtual bool save( std::fstream &file ) const;
 
 virtual bool load( std::fstream &file );
 
 virtual bool recomputeNullRejectionThresholds();
 
 UINT getNumMixtureModels();
 
 Vector< MixtureModel > getModels();
 
 bool setNumMixtureModels(UINT K);
 
 bool setMinChange(Float minChange);
 
 bool setMaxIter(UINT maxIter);
 
 //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_;
 
protected:
 Float computeMixtureLikelihood(const VectorFloat &x,UINT k);
 bool loadLegacyModelFromFile( std::fstream &file );
 
 UINT numMixtureModels;
 UINT maxIter;
 Float minChange;
 Vector< MixtureModel > models;
 
 DebugLog debugLog;
 ErrorLog errorLog;
 WarningLog warningLog;
 
 static RegisterClassifierModule< GMM > registerModule;
 
};

GRT_END_NAMESPACE

#endif //GRT_GMM_HEADER