| allocator_type typedef | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| bn_ | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | protected |
| clone() const override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | virtual |
| clone(const allocator_type &alloc) const override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | virtual |
| column_types_ | gum::learning::DBRowGenerator< ALLOC > | protected |
| columns_of_interest_ | gum::learning::DBRowGenerator< ALLOC > | protected |
| columnsOfInterest() const | gum::learning::DBRowGenerator< ALLOC > | |
| computeRows_(const DBRow< DBTranslatedValue, ALLOC > &row) override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | protectedvirtual |
| DBRowGenerator(const std::vector< DBTranslatedValueType, ALLOC< DBTranslatedValueType > > column_types, const DBRowGeneratorGoal goal, const allocator_type &alloc=allocator_type()) | gum::learning::DBRowGenerator< ALLOC > | |
| DBRowGenerator(const DBRowGenerator< ALLOC > &from) | gum::learning::DBRowGenerator< ALLOC > | |
| DBRowGenerator(const DBRowGenerator< ALLOC > &from, const allocator_type &alloc) | gum::learning::DBRowGenerator< ALLOC > | |
| DBRowGenerator(DBRowGenerator< ALLOC > &&from) | gum::learning::DBRowGenerator< ALLOC > | |
| DBRowGenerator(DBRowGenerator< ALLOC > &&from, const allocator_type &alloc) | gum::learning::DBRowGenerator< ALLOC > | |
| DBRowGeneratorEM(const std::vector< DBTranslatedValueType, ALLOC< DBTranslatedValueType > > column_types, const BayesNet< GUM_SCALAR > &bn, 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::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorEM(const DBRowGeneratorEM< GUM_SCALAR, ALLOC > &from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorEM(const DBRowGeneratorEM< GUM_SCALAR, ALLOC > &from, const allocator_type &alloc) | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorEM(DBRowGeneratorEM< GUM_SCALAR, ALLOC > &&from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorEM(DBRowGeneratorEM< GUM_SCALAR, ALLOC > &&from, const allocator_type &alloc) | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorWithBN(const std::vector< DBTranslatedValueType, ALLOC< DBTranslatedValueType > > column_types, const BayesNet< GUM_SCALAR > &bn, const DBRowGeneratorGoal goal, 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::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorWithBN(const DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > &from) | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorWithBN(const DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > &from, const allocator_type &alloc) | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorWithBN(DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > &&from) | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | |
| DBRowGeneratorWithBN(DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > &&from, const allocator_type &alloc) | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | |
| decreaseRemainingRows() | gum::learning::DBRowGenerator< ALLOC > | |
| generate() override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | virtual |
| getAllocator() const | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| getBayesNet() const | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | |
| goal() const | gum::learning::DBRowGenerator< ALLOC > | |
| goal_ | gum::learning::DBRowGenerator< ALLOC > | protected |
| hasRows() | gum::learning::DBRowGenerator< ALLOC > | |
| nb_remaining_output_rows_ | gum::learning::DBRowGenerator< ALLOC > | protected |
| nodeId2columns_ | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | protected |
| operator=(const DBRowGeneratorEM< GUM_SCALAR, ALLOC > &from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| operator=(DBRowGeneratorEM< GUM_SCALAR, ALLOC > &&from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| gum::learning::DBRowGeneratorWithBN::operator=(const DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > &from) | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | protected |
| gum::learning::DBRowGeneratorWithBN::operator=(DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > &&from) | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | protected |
| gum::learning::DBRowGenerator::operator=(const DBRowGenerator< ALLOC > &) | gum::learning::DBRowGenerator< ALLOC > | protected |
| gum::learning::DBRowGenerator::operator=(DBRowGenerator< ALLOC > &&) | gum::learning::DBRowGenerator< ALLOC > | protected |
| reset() | gum::learning::DBRowGenerator< ALLOC > | virtual |
| setBayesNet(const BayesNet< GUM_SCALAR > &new_bn) override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | virtual |
| setColumnsOfInterest(const std::vector< std::size_t, ALLOC< std::size_t > > &cols_of_interest) | gum::learning::DBRowGenerator< ALLOC > | virtual |
| setColumnsOfInterest(std::vector< std::size_t, ALLOC< std::size_t > > &&cols_of_interest) | gum::learning::DBRowGenerator< ALLOC > | virtual |
| setInputRow(const DBRow< DBTranslatedValue, ALLOC > &row) | gum::learning::DBRowGenerator< ALLOC > | |
| ~DBRowGenerator() | gum::learning::DBRowGenerator< ALLOC > | virtual |
| ~DBRowGeneratorEM() | gum::learning::DBRowGeneratorEM< GUM_SCALAR, ALLOC > | |
| ~DBRowGeneratorWithBN() | gum::learning::DBRowGeneratorWithBN< GUM_SCALAR, ALLOC > | |
