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KLCovarianceInferenceMethod.h
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1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2014 Wu Lin
4  * All rights reserved.
5  *
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9  * 1. Redistributions of source code must retain the above copyright notice, this
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11  * 2. Redistributions in binary form must reproduce the above copyright notice,
12  * this list of conditions and the following disclaimer in the documentation
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15  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
16  * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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29  *
30  * Code adapted from
31  * http://hannes.nickisch.org/code/approxXX.tar.gz
32  * and Gaussian Process Machine Learning Toolbox
33  * http://www.gaussianprocess.org/gpml/code/matlab/doc/
34  * and the reference paper is
35  * Nickisch, Hannes, and Carl Edward Rasmussen.
36  * "Approximations for Binary Gaussian Process Classification."
37  * Journal of Machine Learning Research 9.10 (2008).
38  *
39  */
40 
41 #ifndef _KLCOVARIANCEINFERENCEMETHOD_H_
42 #define _KLCOVARIANCEINFERENCEMETHOD_H_
43 
44 #include <shogun/lib/config.h>
45 
46 #ifdef HAVE_EIGEN3
48 
49 namespace shogun
50 {
51 
74 {
75 public:
78 
88  CMeanFunction* mean, CLabels* labels, CLikelihoodModel* model);
89 
91 
96  virtual const char* get_name() const { return "KLCovarianceInferenceMethod"; }
97 
103 
110 
121  virtual SGVector<float64_t> get_alpha();
122 
135 
136 protected:
138  virtual void update_approx_cov();
139 
141  virtual void update_alpha();
142 
144  virtual void update_chol();
145 
149  virtual void update_deriv();
150 
157 
164 
173  virtual bool lbfgs_precompute();
174 
187 private:
188  void init();
189 
191  SGVector<float64_t> m_sW;
192 
195 
201 
206 
208  SGVector<float64_t> m_dv;
209 
211  SGVector<float64_t> m_df;
212 
213 };
214 }
215 #endif /* HAVE_EIGEN3 */
216 #endif /* _KLCOVARIANCEINFERENCEMETHOD_H_ */
The Inference Method base class.
virtual void get_gradient_of_nlml_wrt_parameters(SGVector< float64_t > gradient)
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:43
virtual float64_t get_derivative_related_cov(SGMatrix< float64_t > dK)
static CKLCovarianceInferenceMethod * obtain_from_generic(CInferenceMethod *inference)
An abstract class of the mean function.
Definition: MeanFunction.h:49
virtual EInferenceType get_inference_type() const
double float64_t
Definition: common.h:50
The KL approximation inference method class.
The KL approximation inference method class.
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_diagonal_vector()
The Kernel base class.
Definition: Kernel.h:158
The Likelihood model base class.

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