KMeansFeatures.h

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#ifndef GRT_KMEANS_FEATURES_HEADER
#define GRT_KMEANS_FEATURES_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/TimeSeriesClassificationData.h"
#include "../../DataStructures/ClassificationDataStream.h"
#include "../../DataStructures/UnlabelledData.h"

GRT_BEGIN_NAMESPACE
    
class GRT_API KMeansFeatures : public FeatureExtraction{
public:
    KMeansFeatures(const Vector< UINT > numClustersPerLayer = Vector< UINT >(1,100),const Float alpha = 0.2,const bool useScaling = true);
 
    KMeansFeatures(const KMeansFeatures &rhs);
    
    virtual ~KMeansFeatures();
    
    KMeansFeatures& operator=(const KMeansFeatures &rhs);

    virtual bool deepCopyFrom(const FeatureExtraction *featureExtraction) override;
    
    virtual bool computeFeatures(const VectorFloat &inputVector) override;
    
    virtual bool reset() override;
    
    virtual bool save( std::fstream &file ) const override;
    
    virtual bool load( std::fstream &file ) override;

    virtual bool train_(ClassificationData &trainingData) override;

    virtual bool train_(TimeSeriesClassificationData &trainingData) override;

    virtual bool train_(ClassificationDataStream &trainingData) override;

    virtual bool train_(UnlabelledData &trainingData) override;

    virtual bool train_(MatrixFloat &trainingData) override;
    
    bool init( const Vector< UINT > &numClustersPerLayer );
    
    bool projectDataThroughLayer( const VectorFloat &input, VectorFloat &output, const UINT layer );
    
    UINT getNumLayers() const;
    UINT getLayerSize(const UINT layerIndex) const;
    Vector< MatrixFloat > getClusters() const;
    
    //Tell the compiler we are using the following functions from the MLBase class to stop hidden virtual function warnings
    using MLBase::save;
    using MLBase::load;
    using MLBase::train;
    using MLBase::train_;
    using MLBase::predict;
    using MLBase::predict_;

    static std::string getId();
    
protected:
    Float alpha;
    Vector< UINT > numClustersPerLayer;
    Vector< MinMax > ranges;
    Vector< MatrixFloat > clusters;
    
private:
    static RegisterFeatureExtractionModule< KMeansFeatures > registerModule;
    static std::string id;
};

GRT_END_NAMESPACE

#endif //GRT_KMEANS_FEATURES_HEADER