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KNN.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) 2006 Christian Gehl
8  * Written (W) 1999-2009 Soeren Sonnenburg
9  * Written (W) 2011 Sergey Lisitsyn
10  * Written (W) 2012 Fernando José Iglesias García, cover tree support
11  * Copyright (C) 2011 Berlin Institute of Technology and Max-Planck-Society
12  */
13 
14 #ifndef _KNN_H__
15 #define _KNN_H__
16 
17 #include <shogun/lib/config.h>
18 
19 #include <shogun/lib/common.h>
20 #include <shogun/io/SGIO.h>
24 
25 namespace shogun
26 {
27 
28 class CDistanceMachine;
29 
56 class CKNN : public CDistanceMachine
57 {
58  public:
60 
61 
62  CKNN();
63 
70  CKNN(int32_t k, CDistance* d, CLabels* trainlab);
71  virtual ~CKNN();
72 
77  virtual EMachineType get_classifier_type() { return CT_KNN; }
78 
89 
95  virtual CMulticlassLabels* apply_multiclass(CFeatures* data=NULL);
96 
98  virtual float64_t apply_one(int32_t vec_idx)
99  {
100  SG_ERROR("for performance reasons use apply() instead of apply(int32_t vec_idx)\n")
101  return 0;
102  }
103 
108 
114  virtual bool load(FILE* srcfile);
115 
121  virtual bool save(FILE* dstfile);
122 
127  inline void set_k(int32_t k)
128  {
129  ASSERT(k>0)
130  m_k=k;
131  }
132 
137  inline int32_t get_k()
138  {
139  return m_k;
140  }
141 
145  inline void set_q(float64_t q)
146  {
147  ASSERT(q<=1.0 && q>0.0)
148  m_q = q;
149  }
150 
154  inline float64_t get_q() { return m_q; }
155 
159  inline void set_use_covertree(bool use_covertree)
160  {
161  m_use_covertree = use_covertree;
162  }
163 
167  inline bool get_use_covertree() const { return m_use_covertree; }
168 
170  virtual const char* get_name() const { return "KNN"; }
171 
172  protected:
177  virtual void store_model_features();
178 
182  virtual CMulticlassLabels* classify_NN();
183 
187  void init_distance(CFeatures* data);
188 
197  virtual bool train_machine(CFeatures* data=NULL);
198 
199  private:
200  void init();
201 
214  int32_t choose_class(float64_t* classes, int32_t* train_lab);
215 
228  void choose_class_for_multiple_k(int32_t* output, int32_t* classes, int32_t* train_lab, int32_t step);
229 
230  protected:
232  int32_t m_k;
233 
236 
239 
241  int32_t m_num_classes;
242 
244  int32_t m_min_label;
245 
248 };
249 
250 }
251 #endif

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