aGrUM  0.14.1
gum::learning::ScoreAIC< ALLOC > Member List

This is the complete list of members for gum::learning::ScoreAIC< ALLOC >, including all inherited members.

_1log2gum::learning::Score< ALLOC >protected
_apriorigum::learning::Score< ALLOC >protected
_cachegum::learning::Score< ALLOC >protected
_countergum::learning::Score< ALLOC >protected
_empty_idsgum::learning::Score< ALLOC >protected
_marginalize(const NodeId X_id, const std::vector< double, ALLOC< double > > &N_xyz) constgum::learning::Score< ALLOC >protected
_score(const IdSet< ALLOC > &idset) finalgum::learning::ScoreAIC< ALLOC >protectedvirtual
_use_cachegum::learning::Score< ALLOC >protected
allocator_type typedefgum::learning::ScoreAIC< ALLOC >
clear()gum::learning::Score< ALLOC >
clearCache()gum::learning::Score< ALLOC >
clearRanges()gum::learning::Score< ALLOC >
clone() constgum::learning::ScoreAIC< ALLOC >virtual
clone(const allocator_type &alloc) constgum::learning::ScoreAIC< ALLOC >virtual
database() constgum::learning::Score< ALLOC >
getAllocator() constgum::learning::Score< ALLOC >
internalApriori() const finalgum::learning::ScoreAIC< ALLOC >virtual
isAprioriCompatible() const finalgum::learning::ScoreAIC< ALLOC >virtual
isAprioriCompatible(const std::string &apriori_type, double weight=1.0f)gum::learning::ScoreAIC< ALLOC >static
isAprioriCompatible(const Apriori< ALLOC > &apriori)gum::learning::ScoreAIC< ALLOC >static
isUsingCache() constgum::learning::Score< ALLOC >
minNbRowsPerThread() constgum::learning::Score< ALLOC >virtual
nbThreads() constgum::learning::Score< ALLOC >virtual
nodeId2Columns() constgum::learning::Score< ALLOC >
operator=(const ScoreAIC< ALLOC > &from)gum::learning::ScoreAIC< ALLOC >
operator=(ScoreAIC< ALLOC > &&from)gum::learning::ScoreAIC< ALLOC >
gum::learning::Score::operator=(const Score< ALLOC > &from)gum::learning::Score< ALLOC >protected
gum::learning::Score::operator=(Score< ALLOC > &&from)gum::learning::Score< ALLOC >protected
ranges() constgum::learning::Score< ALLOC >
Score(const DBRowGeneratorParser< ALLOC > &parser, const Apriori< ALLOC > &external_apriori, const std::vector< std::pair< std::size_t, std::size_t >, ALLOC< std::pair< std::size_t, std::size_t > > > &ranges, 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())gum::learning::Score< ALLOC >
Score(const DBRowGeneratorParser< ALLOC > &parser, const Apriori< ALLOC > &external_apriori, 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())gum::learning::Score< ALLOC >
Score(const Score< ALLOC > &from)gum::learning::Score< ALLOC >protected
Score(const Score< ALLOC > &from, const allocator_type &alloc)gum::learning::Score< ALLOC >protected
Score(Score< ALLOC > &&from)gum::learning::Score< ALLOC >protected
Score(Score< ALLOC > &&from, const allocator_type &alloc)gum::learning::Score< ALLOC >protected
score(const NodeId var)gum::learning::Score< ALLOC >
score(const NodeId var, const std::vector< NodeId, ALLOC< NodeId > > &rhs_ids)gum::learning::Score< ALLOC >
ScoreAIC(const DBRowGeneratorParser< ALLOC > &parser, const Apriori< ALLOC > &apriori, const std::vector< std::pair< std::size_t, std::size_t >, ALLOC< std::pair< std::size_t, std::size_t > > > &ranges, 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())gum::learning::ScoreAIC< ALLOC >
ScoreAIC(const DBRowGeneratorParser< ALLOC > &parser, const Apriori< ALLOC > &apriori, 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())gum::learning::ScoreAIC< ALLOC >
ScoreAIC(const ScoreAIC< ALLOC > &from)gum::learning::ScoreAIC< ALLOC >
ScoreAIC(const ScoreAIC< ALLOC > &from, const allocator_type &alloc)gum::learning::ScoreAIC< ALLOC >
ScoreAIC(ScoreAIC< ALLOC > &&from)gum::learning::ScoreAIC< ALLOC >
ScoreAIC(ScoreAIC< ALLOC > &&from, const allocator_type &alloc)gum::learning::ScoreAIC< ALLOC >
setMaxNbThreads(std::size_t nb) constgum::learning::Score< ALLOC >virtual
setMinNbRowsPerThread(const std::size_t nb) constgum::learning::Score< ALLOC >virtual
setRanges(const std::vector< std::pair< std::size_t, std::size_t >, XALLOC< std::pair< std::size_t, std::size_t > > > &new_ranges)gum::learning::Score< ALLOC >
useCache(const bool on_off)gum::learning::Score< ALLOC >
~Score()gum::learning::Score< ALLOC >virtual
~ScoreAIC()gum::learning::ScoreAIC< ALLOC >virtual