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/*********************************************************************
MLDemos: A User-Friendly visualization toolkit for machine learning
Copyright (C) 2010 Basilio Noris
Contact: mldemos@b4silio.com
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public License,
version 3 as published by the Free Software Foundation.
This library is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free
Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*********************************************************************/
#ifndef _KMEANS_H_
#define _KMEANS_H_
#include <vector>
struct ClusterPoint{
fvec point;
u32 cluster;
float *weights;
ClusterPoint() : point(0,0), cluster(0), weights(NULL){}
~ClusterPoint()
{
if(weights) delete [] weights;
weights=0;
};
};
inline float SquareNorm(fvec p1, fvec p2);
inline int FindSmallest(fvec values);
inline void Mean(std::vector<ClusterPoint>, std::vector<fvec> means, int nbClusters);
inline void SoftMean(std::vector<ClusterPoint> &points, std::vector<fvec> means, int nbClusters);
class KMeansCluster
{
private:
float beta;
u32 clusters;
bool bSoft;
std::vector<fvec> means;
std::vector<ClusterPoint> points;
ivec closestIndices;
int dim;
int power;
bool plusPlus;
bool bGMM;
double **sigma;
double *pi;
public:
KMeansCluster(u32 cnt=1);
~KMeansCluster();
void Update(bool bFirstIteration=false);
void Clear();
void Test(fvec sample, fvec &res);
void SetPoint(u32 index, fvec point){if(index<points.size()) points[index].point = point;}
void AddPoint(fvec sample);
void AddPoints(std::vector<fvec> points);
fvec GetMean(u32 index=0) {return index<clusters ? means[index] : fvec();}
std::vector<fvec> GetMeans(){return means;}
ivec GetClosestPoints();
void SetClusters(u32 clusters);
u32 GetClusters(){return clusters;}
void InitClusters();
void InitClustersPlusPlus();
inline float Distance(fvec a, fvec b);
inline float Distance2(fvec a, fvec b);
void SetSoft(bool soft){bSoft = soft;}
void SetBeta(float b){beta = b > 0 ? b : 0.01f;}
void SetGMM(bool gmm){bGMM = gmm;}
void SetPower(int p){power = p;}
void SetPlusPlus(bool p){plusPlus = p;}
float GetBeta(){return beta;}
private:
void Mean(std::vector<ClusterPoint> &points, std::vector<fvec> &means, int nbClusters);
void SoftMean(std::vector<ClusterPoint> &points, std::vector<fvec> &means, int nbClusters);
void KmeansClustering(std::vector<ClusterPoint> &points, std::vector<fvec> &oldMeans, int nbClusters);
void SoftKmeansClustering(std::vector<ClusterPoint> &points, std::vector<fvec> &oldMeans, int nbClusters, float beta, bool bEStep);
void GMMClustering(std::vector<ClusterPoint> &points, std::vector<fvec> &oldMeans, double **oldSigma, double*oldPi, int nbClusters, bool bEStep);
};
#endif // _KMEANS_H_
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