aGrUM 2.3.2
a C++ library for (probabilistic) graphical models
kNML_inl.h
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40#pragma once
41
42
49
50#ifndef DOXYGEN_SHOULD_SKIP_THIS
51
52namespace gum {
53
54 namespace learning {
55
57 INLINE KNML::KNML(const DBRowGeneratorParser& parser,
58 const Prior& prior,
59 const std::vector< std::pair< std::size_t, std::size_t > >& ranges,
60 const Bijection< NodeId, std::size_t >& nodeId2columns) :
61 IndependenceTest(parser, prior, ranges, nodeId2columns) {
62 GUM_CONSTRUCTOR(KNML);
63 }
64
66 INLINE KNML::KNML(const DBRowGeneratorParser& parser,
67 const Prior& prior,
68 const Bijection< NodeId, std::size_t >& nodeId2columns) :
69 IndependenceTest(parser, prior, nodeId2columns) {
70 GUM_CONSTRUCTOR(KNML);
71 }
72
74 INLINE KNML::KNML(const KNML& from) :
75 IndependenceTest(from), _param_complexity_(from._param_complexity_) {
76 GUM_CONS_CPY(KNML);
77 }
78
80 INLINE KNML::KNML(KNML&& from) :
81 IndependenceTest(std::move(from)), _param_complexity_(std::move(from._param_complexity_)) {
82 GUM_CONS_MOV(KNML);
83 }
84
86 INLINE KNML* KNML::clone() const { return new KNML(*this); }
87
89 INLINE KNML::~KNML() { GUM_DESTRUCTOR(KNML); }
90
91
92 } /* namespace learning */
93
94} /* namespace gum */
95
96#endif /* DOXYGEN_SHOULD_SKIP_THIS */
the class used to read a row in the database and to transform it into a set of DBRow instances that c...
The base class for all the independence tests used for learning.
KNML(const DBRowGeneratorParser &parser, const Prior &prior, const std::vector< std::pair< std::size_t, std::size_t > > &ranges, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
the base class for all a priori
Definition prior.h:83
include the inlined functions if necessary
Definition CSVParser.h:54
gum is the global namespace for all aGrUM entities
Definition agrum.h:46
STL namespace.