| bn_ | gum::learning::DBRowGeneratorWithBN< double > | protected |
| clone() const final | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | virtual |
| column_types_ | gum::learning::DBRowGenerator | protected |
| columns_of_interest_ | gum::learning::DBRowGenerator | protected |
| columnsOfInterest() const | gum::learning::DBRowGenerator | |
| computeRows_(const DBRow< DBTranslatedValue > &row) override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | protectedvirtual |
| 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 | |
| DBRowGeneratorEM(const std::vector< DBTranslatedValueType > &column_types, const BayesNet< GUM_SCALAR > &bn, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >()) | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | |
| DBRowGeneratorEM(const DBRowGeneratorEM< GUM_SCALAR > &from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | |
| DBRowGeneratorEM(DBRowGeneratorEM< GUM_SCALAR > &&from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | |
| DBRowGeneratorWithBN(const std::vector< DBTranslatedValueType > &column_types, const BayesNet< double > &bn, const DBRowGeneratorGoal goal, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >()) | gum::learning::DBRowGeneratorWithBN< double > | |
| decreaseRemainingRows() | gum::learning::DBRowGenerator | |
| generate() override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | virtual |
| getBayesNet() const | gum::learning::DBRowGeneratorWithBN< double > | |
| goal() const | gum::learning::DBRowGenerator | |
| goal_ | gum::learning::DBRowGenerator | protected |
| hasRows() | gum::learning::DBRowGenerator | |
| nb_remaining_output_rows_ | gum::learning::DBRowGenerator | protected |
| nodeId2columns_ | gum::learning::DBRowGeneratorWithBN< double > | protected |
| operator=(const DBRowGeneratorEM< GUM_SCALAR > &from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | |
| operator=(DBRowGeneratorEM< GUM_SCALAR > &&from) | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | |
| gum::learning::DBRowGeneratorWithBN< double >::operator=(const DBRowGeneratorWithBN< double > &from) | gum::learning::DBRowGeneratorWithBN< double > | protected |
| gum::learning::DBRowGenerator::operator=(const DBRowGenerator &) | gum::learning::DBRowGenerator | protected |
| gum::learning::DBRowGenerator::operator=(DBRowGenerator &&) | gum::learning::DBRowGenerator | protected |
| reset() | gum::learning::DBRowGenerator | virtual |
| setBayesNet(const BayesNet< GUM_SCALAR > &new_bn) override final | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | virtual |
| gum::learning::DBRowGeneratorWithBN< double >::setBayesNet(const BayesNet< double > &new_bn) | gum::learning::DBRowGeneratorWithBN< double > | virtual |
| setColumnsOfInterest(const std::vector< std::size_t > &cols_of_interest) | gum::learning::DBRowGenerator | virtual |
| setColumnsOfInterest(std::vector< std::size_t > &&cols_of_interest) | gum::learning::DBRowGenerator | virtual |
| setInputRow(const DBRow< DBTranslatedValue > &row) | gum::learning::DBRowGenerator | |
| ~DBRowGenerator() | gum::learning::DBRowGenerator | virtual |
| ~DBRowGeneratorEM() | gum::learning::DBRowGeneratorEM< GUM_SCALAR > | |
| ~DBRowGeneratorWithBN() | gum::learning::DBRowGeneratorWithBN< double > | |
