| AbstractModel() | shark::AbstractModel< RealVector, RealVector > | inline |
| Autoencoder() | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| BatchInputType typedef | shark::AbstractModel< RealVector, RealVector > | |
| BatchOutputType typedef | shark::AbstractModel< RealVector, RealVector > | |
| BOOST_SERIALIZATION_SPLIT_MEMBER() | shark::ISerializable | |
| createState() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| decode(Data< RealVector > const &patterns) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| decode(LabeledData< RealVector, Label > const &data) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| decoderMatrix() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| decoderMatrix() | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| encode(Data< RealVector > const &patterns) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| encode(LabeledData< RealVector, Label > const &data) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| encoderMatrix() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| encoderMatrix() | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| eval(RealMatrix const &patterns, RealMatrix &output, State &state) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| AbstractModel< RealVector, RealVector >::eval(BatchInputType const &patterns, BatchOutputType &outputs) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| AbstractModel< RealVector, RealVector >::eval(BatchInputType const &patterns, BatchOutputType &outputs, State &state) const=0 | shark::AbstractModel< RealVector, RealVector > | pure virtual |
| AbstractModel< RealVector, RealVector >::eval(InputType const &pattern, OutputType &output) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| evalLayer(std::size_t layer, RealMatrix const &patterns, RealMatrix &outputs) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| evalLayer(std::size_t layer, Data< RealVector > const &patterns) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| Feature enum name | shark::AbstractModel< RealVector, RealVector > | |
| FeatureNotAvailableException typedef | shark::AbstractModel< RealVector, RealVector > | |
| Features typedef | shark::AbstractModel< RealVector, RealVector > | |
| features() const | shark::AbstractModel< RealVector, RealVector > | inline |
| HAS_FIRST_INPUT_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| HAS_FIRST_PARAMETER_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| HAS_SECOND_INPUT_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| HAS_SECOND_PARAMETER_DERIVATIVE enum value | shark::AbstractModel< RealVector, RealVector > | |
| hasFirstInputDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hasFirstParameterDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hasSecondInputDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hasSecondParameterDerivative() const | shark::AbstractModel< RealVector, RealVector > | inline |
| hiddenActivationFunction() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| hiddenActivationFunction() | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| hiddenBias() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| hiddenBias() | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| hiddenResponses(State const &state) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| inputSize() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| InputType typedef | shark::AbstractModel< RealVector, RealVector > | |
| IS_SEQUENTIAL enum value | shark::AbstractModel< RealVector, RealVector > | |
| isSequential() const | shark::AbstractModel< RealVector, RealVector > | inline |
| load(InArchive &archive, unsigned int version) | shark::ISerializable | inline |
| m_features | shark::AbstractModel< RealVector, RealVector > | protected |
| name() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| numberOfHiddenNeurons() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| numberOfParameters() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| operator()(Data< InputType > const &patterns) const | shark::AbstractModel< RealVector, RealVector > | inline |
| operator()(InputType const &pattern) const | shark::AbstractModel< RealVector, RealVector > | inline |
| operator()(BatchInputType const &patterns) const | shark::AbstractModel< RealVector, RealVector > | inline |
| outputActivationFunction() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| outputActivationFunction() | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| outputBias() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| outputBias() | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| outputSize() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| OutputType typedef | shark::AbstractModel< RealVector, RealVector > | |
| parameterVector() const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| read(InArchive &archive) | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| save(OutArchive &archive, unsigned int version) const | shark::ISerializable | inline |
| setParameterVector(RealVector const &newParameters) | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| setStructure(std::size_t in, std::size_t hidden) | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| updateFeatures() | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| weightedDerivatives(BatchInputType const &patterns, BatchOutputType const &coefficients, State const &state, RealVector ¶meterDerivative, BatchInputType &inputDerivative) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| weightedInputDerivative(BatchInputType const &patterns, RealMatrix const &coefficients, State const &state, BatchInputType &inputDerivative) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| AbstractModel< RealVector, RealVector >::weightedInputDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, BatchInputType &derivative) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| AbstractModel< RealVector, RealVector >::weightedInputDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, typename Batch< RealMatrix >::type const &errorHessian, State const &state, RealMatrix &derivative, Batch< RealMatrix >::type &hessian) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| weightedParameterDerivative(BatchInputType const &patterns, RealMatrix const &coefficients, State const &state, RealVector &gradient) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inline |
| AbstractModel< RealVector, RealVector >::weightedParameterDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, RealVector &derivative) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| AbstractModel< RealVector, RealVector >::weightedParameterDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, Batch< RealMatrix >::type const &errorHessian, State const &state, RealVector &derivative, RealMatrix &hessian) const | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| write(OutArchive &archive) const | shark::Autoencoder< HiddenNeuron, OutputNeuron > | inlinevirtual |
| ~AbstractModel() | shark::AbstractModel< RealVector, RealVector > | inlinevirtual |
| ~INameable() | shark::INameable | inlinevirtual |
| ~IParameterizable() | shark::IParameterizable | inlinevirtual |
| ~ISerializable() | shark::ISerializable | inlinevirtual |