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Gaussian.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) 2011 Alesis Novik
8  * Copyright (C) 2011 Berlin Institute of Technology and Max-Planck-Society
9  */
10 
11 #ifndef _GAUSSIAN_H__
12 #define _GAUSSIAN_H__
13 
14 #include <shogun/lib/config.h>
15 
16 #ifdef HAVE_LAPACK
17 
20 #include <shogun/lib/common.h>
23 
24 namespace shogun
25 {
26 class CDotFeatures;
27 
30 {
37 };
38 
46 class CGaussian : public CDistribution
47 {
48  public:
50  CGaussian();
58  virtual ~CGaussian();
59 
61  void init();
62 
69  virtual bool train(CFeatures* data=NULL);
70 
75  virtual int32_t get_num_model_parameters();
76 
82  virtual float64_t get_log_model_parameter(int32_t num_param);
83 
91  int32_t num_param, int32_t num_example);
92 
100  virtual float64_t get_log_likelihood_example(int32_t num_example);
101 
108  {
109  return CMath::exp(compute_log_PDF(point));
110  }
111 
118 
123  virtual SGVector<float64_t> get_mean();
124 
129  virtual void set_mean(const SGVector<float64_t> mean);
130 
135  virtual SGMatrix<float64_t> get_cov();
136 
143  virtual void set_cov(SGMatrix<float64_t> cov);
144 
150  {
151  return m_cov_type;
152  }
153 
160  inline void set_cov_type(ECovType cov_type)
161  {
162  m_cov_type = cov_type;
163  }
164 
170  {
171  return m_d;
172  }
173 
178  void set_d(const SGVector<float64_t> d);
179 
185  {
186  return m_u;
187  }
188 
193  inline void set_u(SGMatrix<float64_t> u)
194  {
195  m_u = u;
196  }
197 
203 
208  static CGaussian* obtain_from_generic(CDistribution* distribution);
209 
211  virtual const char* get_name() const { return "Gaussian"; }
212 
213  private:
215  void register_params();
216 
221  void decompose_cov(SGMatrix<float64_t> cov);
222 
223  protected:
234 };
235 }
236 #endif //HAVE_LAPACK
237 #endif //_GAUSSIAN_H__
SGVector< float64_t > sample()
Definition: Gaussian.cpp:257
float64_t m_constant
Definition: Gaussian.h:225
void set_u(SGMatrix< float64_t > u)
Definition: Gaussian.h:193
Gaussian distribution interface.
Definition: Gaussian.h:46
ECovType get_cov_type()
Definition: Gaussian.h:149
virtual bool train(CFeatures *data=NULL)
Definition: Gaussian.cpp:61
virtual float64_t compute_log_PDF(SGVector< float64_t > point)
Definition: Gaussian.cpp:113
Base class Distribution from which all methods implementing a distribution are derived.
Definition: Distribution.h:41
ECovType m_cov_type
Definition: Gaussian.h:233
full covariance
Definition: Gaussian.h:32
spherical covariance
Definition: Gaussian.h:36
virtual float64_t compute_PDF(SGVector< float64_t > point)
Definition: Gaussian.h:107
SGMatrix< float64_t > m_u
Definition: Gaussian.h:229
virtual SGVector< float64_t > get_mean()
Definition: Gaussian.cpp:152
virtual float64_t get_log_model_parameter(int32_t num_param)
Definition: Gaussian.cpp:93
SGMatrix< float64_t > get_u()
Definition: Gaussian.h:184
static CGaussian * obtain_from_generic(CDistribution *distribution)
Definition: Gaussian.cpp:308
virtual void set_cov(SGMatrix< float64_t > cov)
Definition: Gaussian.cpp:165
double float64_t
Definition: common.h:48
ECovType
Definition: Gaussian.h:29
SGVector< float64_t > m_mean
Definition: Gaussian.h:231
virtual SGMatrix< float64_t > get_cov()
Definition: Gaussian.cpp:179
void set_cov_type(ECovType cov_type)
Definition: Gaussian.h:160
virtual ~CGaussian()
Definition: Gaussian.cpp:57
diagonal covariance
Definition: Gaussian.h:34
virtual float64_t get_log_likelihood_example(int32_t num_example)
Definition: Gaussian.cpp:105
virtual const char * get_name() const
Definition: Gaussian.h:211
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:16
The class Features is the base class of all feature objects.
Definition: Features.h:62
static float64_t exp(float64_t x)
Definition: Math.h:359
SGVector< float64_t > get_d()
Definition: Gaussian.h:169
virtual void set_mean(const SGVector< float64_t > mean)
Definition: Gaussian.cpp:157
virtual int32_t get_num_model_parameters()
Definition: Gaussian.cpp:79
virtual float64_t get_log_derivative(int32_t num_param, int32_t num_example)
Definition: Gaussian.cpp:99
void set_d(const SGVector< float64_t > d)
Definition: Gaussian.cpp:173
SGVector< float64_t > m_d
Definition: Gaussian.h:227

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