aGrUM 3.1.1
a C++ library for (probabilistic) graphical models
EMApproximationScheme.h
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41
47#ifndef GUM_LEARNING_EM_APPROX_SCHEME_H
48#define GUM_LEARNING_EM_APPROX_SCHEME_H
49
50#include <algorithm>
51#include <string>
52#include <vector>
53
54#include <agrum/agrum.h>
55
58
59namespace gum {
60
61 namespace learning {
62
69 public:
74 explicit EMApproximationScheme(bool verbosity = false);
75
76 ~EMApproximationScheme() override = default;
77
86 void setEpsilon(double eps) override;
87
96 void setMinDiffEpsilon(double eps);
97
106 void setMinEpsilonRate(double rate) override;
107 };
108
109 } // namespace learning
110
111} // namespace gum
112
113#ifndef GUM_NO_INLINE
115#endif
116
117#endif // GUM_LEARNING_EM_APPROX_SCHEME_H
gum::ApproximationSchemeListener header file.
This file contains general scheme for iteratively convergent algorithms.
ApproximationScheme(bool verbosity=false)
bool verbosity() const override
Returns true if verbosity is enabled.
void setMinDiffEpsilon(double eps)
sets the stopping criterion of EM as being the minimal difference between two consecutive log-likelih...
void setMinEpsilonRate(double rate) override
sets the stopping criterion of EM as being the minimal log-likelihood's evolution rate
~EMApproximationScheme() override=default
void setEpsilon(double eps) override
sets the stopping criterion of EM as being the minimal difference between two consecutive log-likelih...
EMApproximationScheme(bool verbosity=false)
initializes the EM parameter learning approximation with the min rate criterion
include the inlined functions if necessary
Definition CSVParser.h:55
gum is the global namespace for all aGrUM entities
Definition agrum.h:46