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 |