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StudentsTVGLikelihood.cpp
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1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2014 Wu Lin
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5  *
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29  *
30  * Code adapted from
31  * http://hannes.nickisch.org/code/approxXX.tar.gz
32  * and the reference paper is
33  * Nickisch, Hannes, and Carl Edward Rasmussen.
34  * "Approximations for Binary Gaussian Process Classification."
35  * Journal of Machine Learning Research 9.10 (2008).
36  *
37  * This code specifically adapted from function in approxKL.m
38  */
39 
41 
42 #ifdef HAVE_EIGEN3
44 
45 using namespace Eigen;
46 
47 namespace shogun
48 {
49 
50 CStudentsTVGLikelihood::CStudentsTVGLikelihood()
52 {
53  m_sigma = 1.0;
54  m_df = 3.0;
55  init();
56 }
57 
60 {
61  REQUIRE(sigma>0.0, "Scale parameter must be greater than zero\n")
62  REQUIRE(df>1.0, "Number of degrees of freedom must be greater than one\n")
63 
64  m_sigma=sigma;
65  m_df=df;
66  init();
67 }
68 
70 {
71 }
72 
74 {
75  set_likelihood(new CStudentsTLikelihood(m_sigma, m_df));
76 }
77 
78 void CStudentsTVGLikelihood::init()
79 {
81  SG_ADD(&m_df, "df", "Degrees of freedom", MS_AVAILABLE, GRADIENT_AVAILABLE);
82  SG_ADD(&m_sigma, "sigma", "Scale parameter", MS_AVAILABLE, GRADIENT_AVAILABLE);
83 }
84 
85 } /* namespace shogun */
86 
87 #endif /* HAVE_EIGEN3 */
Definition: SGMatrix.h:20
#define REQUIRE(x,...)
Definition: SGIO.h:206
virtual void set_likelihood(CLikelihoodModel *lik)
double float64_t
Definition: common.h:50
Class that models a Student's-t likelihood.
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
#define SG_ADD(...)
Definition: SGObject.h:81
Class that models likelihood and uses numerical integration to approximate the following variational ...

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