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SingleLaplacianInferenceMethod.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) 2013 Roman Votyakov
8  * Copyright (C) 2012 Jacob Walker
9  * Copyright (C) 2013 Roman Votyakov
10  *
11  * Code adapted from Gaussian Process Machine Learning Toolbox
12  * http://www.gaussianprocess.org/gpml/code/matlab/doc/
13  */
14 
15 #ifndef CSINGLELAPLACIANINFERENCEMETHOD_H_
16 #define CSINGLELAPLACIANINFERENCEMETHOD_H_
17 
18 #include <shogun/lib/config.h>
19 
20 #ifdef HAVE_EIGEN3
21 
23 
24 namespace shogun
25 {
26 
44 {
45 public:
48 
58  CMeanFunction* mean, CLabels* labels, CLikelihoodModel* model);
59 
61 
66  virtual const char* get_name() const { return "SingleLaplacianInferenceMethod"; }
67 
80 
85  virtual bool supports_regression() const
86  {
87  check_members();
88  return m_model->supports_regression();
89  }
90 
95  virtual bool supports_binary() const
96  {
97  check_members();
98  return m_model->supports_binary();
99  }
100 
113 
114 protected:
116  virtual void update_alpha();
117 
119  virtual void update_chol();
120 
122  virtual void update_approx_cov();
123 
127  virtual void update_deriv();
128 
137  const TParameter* param);
138 
147  const TParameter* param);
148 
157  const TParameter* param);
158 
167  const TParameter* param);
168 
169 private:
170  void init();
171 
172 protected:
175 
178 
181 
183 
185 
187 };
188 }
189 #endif /* HAVE_EIGEN3 */
190 #endif /* CSINGLELAPLACIANINFERENCEMETHOD_H_ */
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:43
parameter struct
Definition: Parameter.h:32
The Laplace approximation inference method base class.
An abstract class of the mean function.
Definition: MeanFunction.h:28
virtual SGVector< float64_t > get_derivative_wrt_mean(const TParameter *param)
The SingleLaplace approximation inference method class for regression and binary Classification.
virtual SGVector< float64_t > get_derivative_wrt_inference_method(const TParameter *param)
virtual SGVector< float64_t > get_derivative_wrt_likelihood_model(const TParameter *param)
double float64_t
Definition: common.h:50
virtual bool supports_regression() const
virtual bool supports_binary() const
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
The class Features is the base class of all feature objects.
Definition: Features.h:68
virtual SGVector< float64_t > get_derivative_wrt_kernel(const TParameter *param)
virtual void check_members() const
The Kernel base class.
Definition: Kernel.h:153
The Likelihood model base class.
CLikelihoodModel * m_model

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