ContinuousHiddenMarkovModel.h

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#ifndef GRT_CONTINUOUS_HIDDEN_MARKOV_MODEL_HEADER
#define GRT_CONTINUOUS_HIDDEN_MARKOV_MODEL_HEADER

#include "HMMEnums.h"
#include "../../Util/GRTCommon.h"
#include "../../CoreModules/MLBase.h"

GRT_BEGIN_NAMESPACE

class GRT_API ContinuousHiddenMarkovModel : public MLBase {
    public:
    ContinuousHiddenMarkovModel(const UINT downsampleFactor = 5,const UINT delta = 1,const bool autoEstimateSigma = true,const Float sigma = 10.0);
    
    ContinuousHiddenMarkovModel(const ContinuousHiddenMarkovModel &rhs);
    
    virtual ~ContinuousHiddenMarkovModel();
    
    ContinuousHiddenMarkovModel& operator=(const ContinuousHiddenMarkovModel &rhs);
    
    virtual bool predict_(VectorFloat &x) override;
    virtual bool predict_(MatrixFloat &obs) override;
    
    virtual bool train_(TimeSeriesClassificationSample &trainingData);
    
    virtual bool reset() override;
    
    virtual bool clear() override;
    
    virtual bool save( std::fstream &file ) const override;
    
    virtual bool load( std::fstream &file ) override;
    
    virtual bool print() const override;
    
    UINT getNumStates() const { return numStates; }
    
    UINT getClassLabel() const { return classLabel; }
    
    Float getLoglikelihood() const { return loglikelihood; }
    
    Float getPhase() const { return phase; }
    
    Vector< UINT > getEstimatedStates() const { return estimatedStates; }
    
    MatrixFloat getAlpha() const { return alpha; }
    
    bool setDownsampleFactor(const UINT downsampleFactor);
    
    bool setModelType(const UINT modelType);
    
    bool setDelta(const UINT delta);
    
    bool setSigma(const Float sigma);
    
    bool setAutoEstimateSigma(const bool autoEstimateSigma);
    
    using MLBase::save;
    using MLBase::load;
    using MLBase::train_;
    using MLBase::predict_;
    
protected:
    
    Float gauss( const MatrixFloat &x, const MatrixFloat &y, const MatrixFloat &sigma, const unsigned int i,const unsigned int j,const unsigned int N );
    
    UINT downsampleFactor;
    UINT numStates;             
    UINT classLabel;            
    UINT timeseriesLength;      
    bool autoEstimateSigma;
    Float sigma;
    Float phase;
    MatrixFloat a;             
    MatrixFloat b;             
    VectorFloat pi;            
    MatrixFloat alpha;
    VectorFloat c;
    CircularBuffer< VectorFloat > observationSequence; 
    MatrixFloat obsSequence;
    Vector< UINT > estimatedStates; 
    MatrixFloat sigmaStates; 
    
    UINT modelType;         
    UINT delta;             
    Float loglikelihood;    
    Float cThreshold;       
    
};

GRT_END_NAMESPACE

#endif