SHOGUN  v3.2.0
KMeans.h
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1 /*
2  * This program is free software; you can redistribute it and/or modify
3  * it under the terms of the GNU General Public License as published by
4  * the Free Software Foundation; either version 3 of the License, or
5  * (at your option) any later version.
6  *
7  * Written (W) 1999-2008 Gunnar Raetsch
8  * Written (W) 2007-2009 Soeren Sonnenburg
9  * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
10  */
11 
12 #ifndef _KMEANS_H__
13 #define _KMEANS_H__
14 
15 #include <stdio.h>
16 #include <shogun/lib/common.h>
17 #include <shogun/io/SGIO.h>
21 
22 namespace shogun
23 {
24 class CDistanceMachine;
25 
28 {
31 };
32 
48 class CKMeans : public CDistanceMachine
49 {
50  public:
52  CKMeans();
53 
60  CKMeans(int32_t k, CDistance* d, EKMeansMethod f);
61 
69  CKMeans(int32_t k, CDistance* d, bool kmeanspp=false, EKMeansMethod f=KMM_LLOYD);
70 
77  CKMeans(int32_t k_i, CDistance* d_i, SGMatrix<float64_t> centers_i, EKMeansMethod f=KMM_LLOYD);
78  virtual ~CKMeans();
79 
80 
82 
83 
88 
94  virtual bool load(FILE* srcfile);
95 
101  virtual bool save(FILE* dstfile);
102 
107  void set_k(int32_t p_k);
108 
113  int32_t get_k();
114 
119  void set_use_kmeanspp(bool kmpp);
120 
125  bool get_use_kmeanspp() const;
126 
131  void set_fixed_centers(bool fixed);
132 
137  bool get_fixed_centers();
138 
143  void set_max_iter(int32_t iter);
144 
150 
156 
162 
167  int32_t get_dimensions();
168 
170  virtual const char* get_name() const { return "KMeans"; }
171 
176  virtual void set_initial_centers(SGMatrix<float64_t> centers);
177 
183 
189 
194  void set_mbKMeans_batch_size(int32_t b);
195 
200  int32_t get_mbKMeans_batch_size() const;
201 
206  void set_mbKMeans_iter(int32_t t);
207 
212  int32_t get_mbKMeans_iter() const;
213 
219  void set_mbKMeans_params(int32_t b, int32_t t);
220 
221  private:
230  virtual bool train_machine(CFeatures* data=NULL);
231 
233  virtual void store_model_features();
234 
235  virtual bool train_require_labels() const { return false; }
236 
241  SGMatrix<float64_t> kmeanspp();
242  void init();
243 
248  void set_random_centers(SGVector<float64_t> weights_set, SGVector<int32_t> ClList, int32_t XSize);
249  void set_initial_centers(SGVector<float64_t> weights_set,
250  SGVector<int32_t> ClList, int32_t XSize);
251  void compute_cluster_variances();
252 
253  private:
255  int32_t max_iter;
256 
258  bool fixed_centers;
259 
261  int32_t k;
262 
264  int32_t dimensions;
265 
268 
270  SGMatrix<float64_t> mus_initial;
271 
273  bool use_kmeanspp;
274 
276  int32_t batch_size;
277 
279  int32_t minib_iter;
280 
283 
285  EKMeansMethod train_method;
286 };
287 }
288 #endif
289 
EMachineType
Definition: Machine.h:33
virtual const char * get_name() const
Definition: KMeans.h:170
EKMeansMethod get_train_method() const
Definition: KMeans.cpp:330
virtual bool save(FILE *dstfile)
Definition: KMeans.cpp:286
void set_mbKMeans_params(int32_t b, int32_t t)
Definition: KMeans.cpp:357
Class Distance, a base class for all the distances used in the Shogun toolbox.
Definition: Distance.h:80
bool get_use_kmeanspp() const
Definition: KMeans.cpp:298
void set_mbKMeans_batch_size(int32_t b)
Definition: KMeans.cpp:335
void set_mbKMeans_iter(int32_t t)
Definition: KMeans.cpp:346
EKMeansMethod
Definition: KMeans.h:27
void set_use_kmeanspp(bool kmpp)
Definition: KMeans.cpp:293
void set_k(int32_t p_k)
Definition: KMeans.cpp:303
int32_t get_dimensions()
Definition: KMeans.cpp:382
A generic DistanceMachine interface.
virtual ~CKMeans()
Definition: KMeans.cpp:64
SGVector< float64_t > get_radiuses()
Definition: KMeans.cpp:365
KMeans clustering, partitions the data into k (a-priori specified) clusters.
Definition: KMeans.h:48
#define MACHINE_PROBLEM_TYPE(PT)
Definition: Machine.h:115
float64_t get_max_iter()
Definition: KMeans.cpp:320
double float64_t
Definition: common.h:48
virtual bool load(FILE *srcfile)
Definition: KMeans.cpp:279
bool get_fixed_centers()
Definition: KMeans.cpp:392
void set_max_iter(int32_t iter)
Definition: KMeans.cpp:314
void set_fixed_centers(bool fixed)
Definition: KMeans.cpp:387
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:16
virtual void set_initial_centers(SGMatrix< float64_t > centers)
Definition: KMeans.cpp:68
virtual EMachineType get_classifier_type()
Definition: KMeans.h:87
The class Features is the base class of all feature objects.
Definition: Features.h:62
int32_t get_mbKMeans_batch_size() const
Definition: KMeans.cpp:341
void set_train_method(EKMeansMethod f)
Definition: KMeans.cpp:325
int32_t get_mbKMeans_iter() const
Definition: KMeans.cpp:352
int32_t get_k()
Definition: KMeans.cpp:309
SGMatrix< float64_t > get_cluster_centers()
Definition: KMeans.cpp:370

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