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 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 saveModelToFile( std::fstream &file ) const;
    
    virtual bool loadModelFromFile( 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::saveModelToFile;
    using MLBase::loadModelFromFile;
    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