euclidean_k_means.h

来自「gmeans-- Clustering with first variation」· C头文件 代码 · 共 37 行

/*   Euclidean k-means header file
     Euclidean_k_means.h
     Copyright (c) 2003, Yuqiang Guan
*/

#if !defined(_Euclidean_K_MEANS_H_)
#define _Euclidean_K_MEANS_H_

#include "Gmeans.h"
#include "mat_vec.h"

class Euclidean_k_means : public Gmeans
{
 public:
  Euclidean_k_means(Matrix *p_docs, int cluster[], int ini_num_clusters, int est_start,	float Omiga, bool random_seeding, int seed, float epsilon);
  ~Euclidean_k_means();
 protected:
  float *norm_CV, *new_norm_CV; //store 2-norms of data vec.
  virtual float delta_X ( Matrix *p_Docs, int x, int j);
  virtual float verify_obj_func(Matrix *p_Docs, int n_clus);
  virtual void  well_separated_centroids(Matrix *p_Docs, int i);
  virtual void  random_centroids(Matrix *p_Docs);
  virtual void  random_perturb_init(Matrix *p_Docs);	
  virtual int   assign_cluster(Matrix *p_Docs, bool simi_est);
  virtual void  general_k_means(Matrix *p_Docs);
  virtual void  remove_Empty_Clusters();
  virtual int   find_worst_vectors(bool dumped);
  virtual void  initialize_cv(Matrix *p_Docs, char * seeding_file);
  float one_f_v_move(Matrix *p_Docs, one_step track [], int step); 
  virtual float K_L_first_variation(Matrix *p_Docs);
  virtual float Split_Clusters(Matrix *p_Docs, int worst_vector,  float s_bar);
  void  update_centroids(Matrix *p_Docs);
 
};

#endif // !defined(_Euclidean_K_MEANS_H_)