| backpropagate(Eigen::MatrixXd *ein, Eigen::MatrixXd *&eout, bool backpropToPrevious) | OpenANN::SparseAutoEncoder | virtual |
| currentParameters() | OpenANN::SparseAutoEncoder | virtual |
| deleteTrainSet | OpenANN::Learner | protected |
| deleteValidSet | OpenANN::Learner | protected |
| dimension() | OpenANN::SparseAutoEncoder | virtual |
| error() | OpenANN::SparseAutoEncoder | virtual |
| OpenANN::Learner::error(unsigned n) | OpenANN::Optimizable | inlinevirtual |
| OpenANN::Learner::error(std::vector< int >::const_iterator startN, std::vector< int >::const_iterator endN) | OpenANN::Optimizable | virtual |
| errorGradient(double &value, Eigen::VectorXd &grad) | OpenANN::SparseAutoEncoder | virtual |
| OpenANN::Learner::errorGradient(int n, double &value, Eigen::VectorXd &grad) | OpenANN::Optimizable | virtual |
| OpenANN::Learner::errorGradient(std::vector< int >::const_iterator startN, std::vector< int >::const_iterator endN, double &value, Eigen::VectorXd &grad) | OpenANN::Optimizable | virtual |
| examples() | OpenANN::Optimizable | inlinevirtual |
| finishedIteration() | OpenANN::Optimizable | inlinevirtual |
| forwardPropagate(Eigen::MatrixXd *x, Eigen::MatrixXd *&y, bool dropout, double *error=0) | OpenANN::SparseAutoEncoder | virtual |
| getInputWeights() | OpenANN::SparseAutoEncoder | |
| getOutput() | OpenANN::SparseAutoEncoder | virtual |
| getOutputWeights() | OpenANN::SparseAutoEncoder | |
| getParameters() | OpenANN::SparseAutoEncoder | virtual |
| gradient() | OpenANN::SparseAutoEncoder | virtual |
| OpenANN::Learner::gradient(unsigned n) | OpenANN::Optimizable | inlinevirtual |
| OpenANN::Learner::gradient(std::vector< int >::const_iterator startN, std::vector< int >::const_iterator endN) | OpenANN::Optimizable | virtual |
| initialize() | OpenANN::SparseAutoEncoder | virtual |
| initialize(std::vector< double * > ¶meterPointers, std::vector< double * > ¶meterDerivativePointers) | OpenANN::SparseAutoEncoder | virtual |
| initializeParameters() | OpenANN::SparseAutoEncoder | virtual |
| Learner() | OpenANN::Learner | |
| N | OpenANN::Learner | protected |
| operator()(const Eigen::VectorXd &x) | OpenANN::SparseAutoEncoder | virtual |
| operator()(const Eigen::MatrixXd &X) | OpenANN::SparseAutoEncoder | virtual |
| providesGradient() | OpenANN::SparseAutoEncoder | virtual |
| providesInitialization() | OpenANN::SparseAutoEncoder | virtual |
| reconstruct(const Eigen::VectorXd &x) | OpenANN::SparseAutoEncoder | |
| removeTrainingSet() | OpenANN::Learner | virtual |
| removeValidationSet() | OpenANN::Learner | virtual |
| setParameters(const Eigen::VectorXd ¶meters) | OpenANN::SparseAutoEncoder | virtual |
| SparseAutoEncoder(int D, int H, double beta, double rho, double lambda, ActivationFunction act) | OpenANN::SparseAutoEncoder | |
| trainingSet(DataSet &trainingSet) | OpenANN::SparseAutoEncoder | virtual |
| OpenANN::Learner::trainingSet(Eigen::MatrixXd &input, Eigen::MatrixXd &output) | OpenANN::Learner | virtual |
| trainSet | OpenANN::Learner | protected |
| updatedParameters() | OpenANN::SparseAutoEncoder | inlinevirtual |
| validationSet(Eigen::MatrixXd &input, Eigen::MatrixXd &output) | OpenANN::Learner | virtual |
| validationSet(DataSet &validationSet) | OpenANN::Learner | virtual |
| validSet | OpenANN::Learner | protected |
| ~Layer() | OpenANN::Layer | inlinevirtual |
| ~Learner() | OpenANN::Learner | virtual |
| ~Optimizable() | OpenANN::Optimizable | inlinevirtual |