KMeans.h

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#ifndef GRT_KMEANS_HEADER
#define GRT_KMEANS_HEADER

#include "../../Util/GRTCommon.h"
#include "../../CoreModules/Clusterer.h"
#include "../../DataStructures/ClassificationData.h"
#include "../../DataStructures/UnlabelledData.h"

GRT_BEGIN_NAMESPACE

class GRT_API KMeans : public Clusterer{

public:
 KMeans(const UINT numClusters=10,const UINT minNumEpochs=5,const UINT maxNumEpochs=1000,const Float minChange=1.0e-5,const bool computeTheta=true);

 KMeans(const KMeans &rhs);
 
 virtual ~KMeans();
 
 KMeans &operator=(const KMeans &rhs);
 
 virtual bool deepCopyFrom(const Clusterer *clusterer);
 
 virtual bool reset();
 
 virtual bool clear();
 
 bool trainModel(MatrixFloat &data);
 
 virtual bool train_(MatrixFloat &data);
 
 virtual bool train_(ClassificationData &trainingData);
 
 virtual bool train_(UnlabelledData &trainingData);
 
 virtual bool predict_(VectorFloat &inputVector);
 
 virtual bool saveModelToFile( std::fstream &file ) const;
 
 virtual bool loadModelFromFile( std::fstream &file );
 
 //bool predict(VectorFloat inputVector,UINT &predictedClusterLabel,Float &maxLikelihood,VectorFloat &clusterLikelihoods);

 //Getters
 Float getTheta(){ return finalTheta; }
 bool getModelTrained(){ return trained; }

 const VectorFloat& getTrainingThetaLog() const { return thetaTracker; }
 const MatrixFloat& getClusters() const { return clusters; }
 const Vector< UINT >& getClassLabelsVector() const { return assign; }
 const Vector< UINT >& getClassCountVector() const { return count; }
 
 //Setters
 bool setComputeTheta(const bool computeTheta);
 
 bool setClusters(const MatrixFloat &clusters);
 
 //Tell the compiler we are using the following functions from the MLBase class to stop hidden virtual function warnings
 using MLBase::saveModelToFile;
 using MLBase::loadModelFromFile;
 using MLBase::train;
 using MLBase::train_;
 using MLBase::predict;
 using MLBase::predict_;

protected:
 UINT estep(const MatrixFloat &data);
 void mstep(const MatrixFloat &data);
 Float calculateTheta(const MatrixFloat &data);
 inline Float SQR(const Float a) {return a*a;};

 bool computeTheta;
 UINT numTrainingSamples; 
 UINT nchg; 
 Float finalTheta;
 MatrixFloat clusters;
 Vector< UINT > assign, count;
 VectorFloat thetaTracker;
 
private:
 static RegisterClustererModule< KMeans > registerModule;
};
 
GRT_END_NAMESPACE

#endif //GRT_KMEANS_HEADER