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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 <stdio.h>
18 #include <shogun/lib/common.h>
19 #include <shogun/io/SGIO.h>
23 
24 namespace shogun
25 {
26 
27 class CDistanceMachine;
28 
55 class CKNN : public CDistanceMachine
56 {
57  public:
59 
60 
61  CKNN();
62 
69  CKNN(int32_t k, CDistance* d, CLabels* trainlab);
70  virtual ~CKNN();
71 
76  virtual EMachineType get_classifier_type() { return CT_KNN; }
77 
88 
94  virtual CMulticlassLabels* apply_multiclass(CFeatures* data=NULL);
95 
97  virtual float64_t apply_one(int32_t vec_idx)
98  {
99  SG_ERROR("for performance reasons use apply() instead of apply(int32_t vec_idx)\n")
100  return 0;
101  }
102 
107 
113  virtual bool load(FILE* srcfile);
114 
120  virtual bool save(FILE* dstfile);
121 
126  inline void set_k(int32_t k)
127  {
128  ASSERT(k>0)
129  m_k=k;
130  }
131 
136  inline int32_t get_k()
137  {
138  return m_k;
139  }
140 
144  inline void set_q(float64_t q)
145  {
146  ASSERT(q<=1.0 && q>0.0)
147  m_q = q;
148  }
149 
153  inline float64_t get_q() { return m_q; }
154 
158  inline void set_use_covertree(bool use_covertree)
159  {
160  m_use_covertree = use_covertree;
161  }
162 
166  inline bool get_use_covertree() const { return m_use_covertree; }
167 
169  virtual const char* get_name() const { return "KNN"; }
170 
171  protected:
176  virtual void store_model_features();
177 
181  virtual CMulticlassLabels* classify_NN();
182 
186  void init_distance(CFeatures* data);
187 
196  virtual bool train_machine(CFeatures* data=NULL);
197 
198  private:
199  void init();
200 
213  int32_t choose_class(float64_t* classes, int32_t* train_lab);
214 
227  void choose_class_for_multiple_k(int32_t* output, int32_t* classes, int32_t* train_lab, int32_t step);
228 
229  protected:
231  int32_t m_k;
232 
235 
238 
240  int32_t m_num_classes;
241 
243  int32_t m_min_label;
244 
247 };
248 
249 }
250 #endif
EMachineType
Definition: Machine.h:33
virtual void store_model_features()
Definition: KNN.cpp:450
virtual bool save(FILE *dstfile)
Definition: KNN.cpp:443
virtual EMachineType get_classifier_type()
Definition: KNN.h:76
Class Distance, a base class for all the distances used in the Shogun toolbox.
Definition: Distance.h:80
void init_distance(CFeatures *data)
Definition: KNN.cpp:422
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:35
float64_t get_q()
Definition: KNN.h:153
SGMatrix< int32_t > classify_for_multiple_k()
Definition: KNN.cpp:333
#define SG_ERROR(...)
Definition: SGIO.h:131
int32_t get_k()
Definition: KNN.h:136
int32_t m_min_label
smallest label, i.e. -1
Definition: KNN.h:243
virtual bool train_machine(CFeatures *data=NULL)
Definition: KNN.cpp:72
void set_q(float64_t q)
Definition: KNN.h:144
SGMatrix< index_t > nearest_neighbors()
Definition: KNN.cpp:109
A generic DistanceMachine interface.
shogun matrix
Definition: DenseFeatures.h:27
virtual bool load(FILE *srcfile)
Definition: KNN.cpp:436
int32_t m_num_classes
number of classes (i.e. number of values labels can take)
Definition: KNN.h:240
Multiclass Labels for multi-class classification.
int32_t m_k
the k parameter in KNN
Definition: KNN.h:231
#define ASSERT(x)
Definition: SGIO.h:203
void set_use_covertree(bool use_covertree)
Definition: KNN.h:158
#define MACHINE_PROBLEM_TYPE(PT)
Definition: Machine.h:115
double float64_t
Definition: common.h:48
Class KNN, an implementation of the standard k-nearest neigbor classifier.
Definition: KNN.h:55
float64_t m_q
parameter q of rank weighting
Definition: KNN.h:234
SGVector< int32_t > m_train_labels
Definition: KNN.h:246
bool get_use_covertree() const
Definition: KNN.h:166
void set_k(int32_t k)
Definition: KNN.h:126
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:16
virtual const char * get_name() const
Definition: KNN.h:169
virtual ~CKNN()
Definition: KNN.cpp:68
The class Features is the base class of all feature objects.
Definition: Features.h:62
virtual CMulticlassLabels * classify_NN()
Definition: KNN.cpp:288
virtual CMulticlassLabels * apply_multiclass(CFeatures *data=NULL)
Definition: KNN.cpp:153
virtual float64_t apply_one(int32_t vec_idx)
get output for example "vec_idx"
Definition: KNN.h:97
bool m_use_covertree
parameter to enable cover tree support
Definition: KNN.h:237

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