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VariationalLikelihood.cpp
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1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2014 Wu Lin
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31 
32 #include <shogun/lib/config.h>
34 
35 namespace shogun
36 {
37 
40 {
41  init();
42 }
43 
45 {
47 }
48 
50 {
52  m_likelihood=lik;
54 }
55 
56 void CVariationalLikelihood::init()
57 {
58  //m_likelihood will be specified by its subclass
59  //via the init_likelihood method
60  m_likelihood = NULL;
62 
63  SG_ADD(&m_lab, "labels",
64  "The label of the data\n",
66 
67  SG_ADD((CSGObject**)&m_likelihood, "likelihood",
68  "The distribution used to model the data\n",
70 }
71 
74  const CLabels* lab) const
75 {
76  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
77  return m_likelihood->get_predictive_means(mu, s2, lab);
78 }
79 
82  const CLabels* lab) const
83 {
84  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
85  return m_likelihood->get_predictive_variances(mu, s2, lab);
86 }
87 
89  const CLabels* lab, SGVector<float64_t> func,
90  const TParameter* param) const
91 {
92  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
93  return m_likelihood->get_first_derivative(lab, func, param);
94 }
95 
97  const CLabels* lab, SGVector<float64_t> func,
98  const TParameter* param) const
99 {
100  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
101  return m_likelihood->get_second_derivative(lab, func, param);
102 }
103 
105  const CLabels* lab, SGVector<float64_t> func,
106  const TParameter* param) const
107 {
108  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
109  return m_likelihood->get_third_derivative(lab, func, param);
110 }
111 
113 {
114  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
115  return m_likelihood->get_model_type();
116 }
117 
119  const CLabels* lab, SGVector<float64_t> func) const
120 {
121  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
122  return m_likelihood->get_log_probability_f(lab, func);
123 }
124 
126  const CLabels* lab, SGVector<float64_t> func, index_t i) const
127 {
128  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
129  return m_likelihood->get_log_probability_derivative_f(lab, func, i);
130 }
131 
134  const CLabels* lab) const
135 {
136  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
137  return m_likelihood->get_log_zeroth_moments(mu, s2, lab);
138 }
139 
142  const CLabels* lab, index_t i) const
143 {
144  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
145  return m_likelihood->get_first_moment(mu, s2, lab, i);
146 }
147 
150  const CLabels* lab, index_t i) const
151 {
152  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
153  return m_likelihood->get_second_moment(mu, s2, lab, i);
154 }
155 
157 {
158  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
160 }
161 
163 {
164  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
165  return m_likelihood->supports_binary();
166 }
167 
169 {
170  REQUIRE(m_likelihood != NULL, "The likelihood should be initialized\n");
172 }
173 
174 }
virtual SGVector< float64_t > get_third_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const
virtual SGVector< float64_t > get_log_probability_f(const CLabels *lab, SGVector< float64_t > func) const =0
ELikelihoodModelType
virtual bool supports_multiclass() const
int32_t index_t
Definition: common.h:62
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:43
virtual SGVector< float64_t > get_second_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const
virtual ELikelihoodModelType get_model_type() const
parameter struct
virtual SGVector< float64_t > get_log_zeroth_moments(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab) const =0
#define REQUIRE(x,...)
Definition: SGIO.h:206
virtual SGVector< float64_t > get_predictive_variances(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const =0
virtual float64_t get_second_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const
virtual float64_t get_second_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const =0
#define SG_REF(x)
Definition: SGObject.h:54
virtual SGVector< float64_t > get_first_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const
virtual void set_likelihood(CLikelihoodModel *lik)
Class SGObject is the base class of all shogun objects.
Definition: SGObject.h:115
virtual SGVector< float64_t > get_predictive_means(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const
double float64_t
Definition: common.h:50
virtual SGVector< float64_t > get_predictive_variances(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const
virtual bool supports_regression() const
virtual bool supports_binary() const
virtual SGVector< float64_t > get_log_probability_f(const CLabels *lab, SGVector< float64_t > func) const
virtual SGVector< float64_t > get_log_probability_derivative_f(const CLabels *lab, SGVector< float64_t > func, index_t i) const
virtual ELikelihoodModelType get_model_type() const
virtual SGVector< float64_t > get_log_zeroth_moments(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab) const
#define SG_UNREF(x)
Definition: SGObject.h:55
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
virtual SGVector< float64_t > get_second_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const
virtual float64_t get_first_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const
virtual SGVector< float64_t > get_log_probability_derivative_f(const CLabels *lab, SGVector< float64_t > func, index_t i) const =0
virtual SGVector< float64_t > get_predictive_means(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab=NULL) const =0
virtual SGVector< float64_t > get_third_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const
#define SG_ADD(...)
Definition: SGObject.h:84
virtual float64_t get_first_moment(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab, index_t i) const =0
virtual SGVector< float64_t > get_first_derivative(const CLabels *lab, SGVector< float64_t > func, const TParameter *param) const
The Likelihood model base class.

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