aGrUM 2.3.2
a C++ library for (probabilistic) graphical models
gum::learning::DBRowGeneratorWithBN< GUM_SCALAR > Member List

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

bn_gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >protected
clone() const =0gum::learning::DBRowGeneratorpure virtual
column_types_gum::learning::DBRowGeneratorprotected
columns_of_interest_gum::learning::DBRowGeneratorprotected
columnsOfInterest() constgum::learning::DBRowGenerator
computeRows_(const DBRow< DBTranslatedValue > &row)=0gum::learning::DBRowGeneratorprotectedpure virtual
DBRowGenerator(const std::vector< DBTranslatedValueType > &column_types, const DBRowGeneratorGoal goal)gum::learning::DBRowGenerator
DBRowGenerator(const DBRowGenerator &from)gum::learning::DBRowGenerator
DBRowGenerator(DBRowGenerator &&from)gum::learning::DBRowGenerator
DBRowGeneratorWithBN(const std::vector< DBTranslatedValueType > &column_types, const BayesNet< GUM_SCALAR > &bn, const DBRowGeneratorGoal goal, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >
DBRowGeneratorWithBN(const DBRowGeneratorWithBN< GUM_SCALAR > &from)gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >
DBRowGeneratorWithBN(DBRowGeneratorWithBN< GUM_SCALAR > &&from)gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >
decreaseRemainingRows()gum::learning::DBRowGenerator
generate()=0gum::learning::DBRowGeneratorpure virtual
getBayesNet() constgum::learning::DBRowGeneratorWithBN< GUM_SCALAR >
goal() constgum::learning::DBRowGenerator
goal_gum::learning::DBRowGeneratorprotected
hasRows()gum::learning::DBRowGenerator
nb_remaining_output_rows_gum::learning::DBRowGeneratorprotected
nodeId2columns_gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >protected
operator=(const DBRowGeneratorWithBN< GUM_SCALAR > &from)gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >protected
operator=(DBRowGeneratorWithBN< GUM_SCALAR > &&from)gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >protected
gum::learning::DBRowGenerator::operator=(const DBRowGenerator &)gum::learning::DBRowGeneratorprotected
gum::learning::DBRowGenerator::operator=(DBRowGenerator &&)gum::learning::DBRowGeneratorprotected
reset()gum::learning::DBRowGeneratorvirtual
setBayesNet(const BayesNet< GUM_SCALAR > &new_bn)gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >virtual
setColumnsOfInterest(const std::vector< std::size_t > &cols_of_interest)gum::learning::DBRowGeneratorvirtual
setColumnsOfInterest(std::vector< std::size_t > &&cols_of_interest)gum::learning::DBRowGeneratorvirtual
setInputRow(const DBRow< DBTranslatedValue > &row)gum::learning::DBRowGenerator
~DBRowGenerator()gum::learning::DBRowGeneratorvirtual
~DBRowGeneratorWithBN()gum::learning::DBRowGeneratorWithBN< GUM_SCALAR >