28 #ifndef GUM_LEARNING_A_PRIORI_K2_H 29 #define GUM_LEARNING_A_PRIORI_K2_H 51 template <
template <
typename >
class ALLOC = std::allocator >
virtual void setWeight(const double weight) final
dummy set weight function: in K2, weights are always equal to 1
AprioriK2(const DatabaseTable< ALLOC > &database, const Bijection< NodeId, std::size_t, ALLOC< std::size_t > > &nodeId2columns=Bijection< NodeId, std::size_t, ALLOC< std::size_t > >(), const allocator_type &alloc=allocator_type())
default constructor
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
virtual AprioriK2< ALLOC > * clone() const
virtual copy constructor
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
virtual ~AprioriK2()
destructor
AprioriK2< ALLOC > & operator=(const AprioriK2< ALLOC > &from)
copy operator
double weight() const
returns the weight assigned to the apriori
Set of pairs of elements with fast search for both elements.
Copyright 2005-2019 Pierre-Henri WUILLEMIN et Christophe GONZALES (LIP6) {prenom.nom}_at_lip6.fr.
The class representing a tabular database as used by learning tasks.
ALLOC< NodeId > allocator_type
type for the allocators passed in arguments of methods
the internal apriori for the K2 score = Laplace AprioriK2 is a BD score with a Laplace apriori (i...
the smooth a priori: adds a weight w to all the countings
ALLOC< NodeId > allocator_type
type for the allocators passed in arguments of methods
Size NodeId
Type for node ids.