aGrUM  0.16.0
greedyHillClimbing.cpp
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1 
30 
31 namespace gum {
32 
33  namespace learning {
34 
37  setEpsilon(0);
41  GUM_CONSTRUCTOR(GreedyHillClimbing);
42  }
43 
46  ApproximationScheme(from) {
47  GUM_CONS_CPY(GreedyHillClimbing);
48  }
49 
52  ApproximationScheme(std::move(from)) {
53  GUM_CONS_MOV(GreedyHillClimbing);
54  }
55 
58  GUM_DESTRUCTOR(GreedyHillClimbing);
59  }
60 
64  ApproximationScheme::operator=(from);
65  return *this;
66  }
67 
70  ApproximationScheme::operator=(std::move(from));
71  return *this;
72  }
73 
76  return *this;
77  }
78 
79  } /* namespace learning */
80 
81 } /* namespace gum */
void disableMinEpsilonRate()
Disable stopping criterion on epsilon rate.
Approximation Scheme.
STL namespace.
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
Definition: agrum.h:25
ApproximationScheme & approximationScheme()
returns the approximation policy of the learning algorithm
void disableMaxTime()
Disable stopping criterion on timeout.
The greedy hill climbing learning algorithm (for directed graphs)
void setEpsilon(double eps)
Given that we approximate f(t), stopping criterion on |f(t+1)-f(t)|.
void disableMaxIter()
Disable stopping criterion on max iterations.
GreedyHillClimbing()
default constructor
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
GreedyHillClimbing & operator=(const GreedyHillClimbing &from)
copy operator