KMeansQuantizer.h

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#ifndef GRT_KMEANS_QUANTIZER_HEADER
#define GRT_KMEANS_QUANTIZER_HEADER

//Include the main GRT header to get access to the FeatureExtraction base class
#include "../../CoreModules/FeatureExtraction.h"
#include "../../ClusteringModules/KMeans/KMeans.h"
#include "../../DataStructures/ClassificationDataStream.h"
#include "../../DataStructures/TimeSeriesClassificationData.h"
#include "../../DataStructures/UnlabelledData.h"

GRT_BEGIN_NAMESPACE
    
class KMeansQuantizer : public FeatureExtraction{
public:
    KMeansQuantizer(const UINT numClusters=10);
 
    KMeansQuantizer(const KMeansQuantizer &rhs);
    
    virtual ~KMeansQuantizer();
    
    KMeansQuantizer& operator=(const KMeansQuantizer &rhs);

    virtual bool deepCopyFrom(const FeatureExtraction *featureExtraction);
    
    virtual bool computeFeatures(const VectorFloat &inputVector);
    
    virtual bool reset();
    
    virtual bool clear();
    
    virtual bool saveModelToFile( std::fstream &file ) const;
    
    virtual bool loadModelFromFile( std::fstream &file );

    virtual bool train_(ClassificationData &trainingData);

    virtual bool train_(TimeSeriesClassificationData &trainingData);

    virtual bool train_(ClassificationDataStream &trainingData);

    virtual bool train_(UnlabelledData &trainingData);

    virtual bool train_(MatrixFloat &trainingData);

 UINT quantize(Float inputValue);
 
 UINT quantize(const VectorFloat &inputVector);
    
    bool getQuantizerTrained() const { return trained; }
    
    UINT getNumClusters() const;

    UINT getQuantizedValue() const { return (trained ? (UINT)featureVector[0] : 0); }
 
 VectorFloat getQuantizationDistances() const{
  return quantizationDistances;
 }
 
 MatrixFloat getQuantizationModel() const{
  return clusters;
 }
    
    bool setNumClusters(const UINT numClusters);
    
    //Tell the compiler we are using the following functions from the FeatureExtractiona and MLBase class to stop hidden virtual function warnings
    using FeatureExtraction::saveModelToFile;
    using FeatureExtraction::loadModelFromFile;
    using MLBase::train;
    using MLBase::train_;
    using MLBase::predict;
    using MLBase::predict_;
    
protected:
    UINT numClusters;
    MatrixFloat clusters;
    VectorFloat quantizationDistances;
    
    static RegisterFeatureExtractionModule< KMeansQuantizer > registerModule;
};

GRT_END_NAMESPACE

#endif //GRT_KMEANS_QUANTIZER_HEADER