shark::FFNet< HiddenNeuron, OutputNeuron > Member List

This is the complete list of members for shark::FFNet< HiddenNeuron, OutputNeuron >, including all inherited members.

AbstractModel()shark::AbstractModel< RealVector, RealVector >inline
backpropMatrices() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
BatchInputType typedefshark::AbstractModel< RealVector, RealVector >
BatchOutputType typedefshark::AbstractModel< RealVector, RealVector >
bias() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
bias(std::size_t layer) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
BOOST_SERIALIZATION_SPLIT_MEMBER()shark::ISerializable
createState() constshark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
eval(RealMatrix const &patterns, RealMatrix &output, State &state) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
AbstractModel< RealVector, RealVector >::eval(BatchInputType const &patterns, BatchOutputType &outputs) constshark::AbstractModel< RealVector, RealVector >inlinevirtual
AbstractModel< RealVector, RealVector >::eval(BatchInputType const &patterns, BatchOutputType &outputs, State &state) const=0shark::AbstractModel< RealVector, RealVector >pure virtual
AbstractModel< RealVector, RealVector >::eval(InputType const &pattern, OutputType &output) constshark::AbstractModel< RealVector, RealVector >inlinevirtual
evalLayer(std::size_t layer, RealMatrix const &patterns, RealMatrix &outputs) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
evalLayer(std::size_t layer, Data< RealVector > const &patterns) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
Feature enum nameshark::AbstractModel< RealVector, RealVector >
FeatureNotAvailableException typedefshark::AbstractModel< RealVector, RealVector >
Features typedefshark::AbstractModel< RealVector, RealVector >
features() constshark::AbstractModel< RealVector, RealVector >inline
FFNet()shark::FFNet< HiddenNeuron, OutputNeuron >inline
HAS_FIRST_INPUT_DERIVATIVE enum valueshark::AbstractModel< RealVector, RealVector >
HAS_FIRST_PARAMETER_DERIVATIVE enum valueshark::AbstractModel< RealVector, RealVector >
HAS_SECOND_INPUT_DERIVATIVE enum valueshark::AbstractModel< RealVector, RealVector >
HAS_SECOND_PARAMETER_DERIVATIVE enum valueshark::AbstractModel< RealVector, RealVector >
hasFirstInputDerivative() constshark::AbstractModel< RealVector, RealVector >inline
hasFirstParameterDerivative() constshark::AbstractModel< RealVector, RealVector >inline
hasSecondInputDerivative() constshark::AbstractModel< RealVector, RealVector >inline
hasSecondParameterDerivative() constshark::AbstractModel< RealVector, RealVector >inline
hiddenActivationFunction() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
hiddenActivationFunction()shark::FFNet< HiddenNeuron, OutputNeuron >inline
inputOutputShortcut() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
inputSize() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
InputType typedefshark::AbstractModel< RealVector, RealVector >
IS_SEQUENTIAL enum valueshark::AbstractModel< RealVector, RealVector >
isSequential() constshark::AbstractModel< RealVector, RealVector >inline
layerMatrices() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
layerMatrix(std::size_t layer) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
load(InArchive &archive, unsigned int version)shark::ISerializableinline
m_featuresshark::AbstractModel< RealVector, RealVector >protected
name() constshark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
neuronResponses(State const &state) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
numberOfHiddenNeurons() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
numberOfNeurons() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
numberOfParameters() constshark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
operator()(Data< InputType > const &patterns) constshark::AbstractModel< RealVector, RealVector >inline
operator()(InputType const &pattern) constshark::AbstractModel< RealVector, RealVector >inline
operator()(BatchInputType const &patterns) constshark::AbstractModel< RealVector, RealVector >inline
outputActivationFunction() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
outputActivationFunction()shark::FFNet< HiddenNeuron, OutputNeuron >inline
outputSize() constshark::FFNet< HiddenNeuron, OutputNeuron >inline
OutputType typedefshark::AbstractModel< RealVector, RealVector >
parameterVector() constshark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
read(InArchive &archive)shark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
save(OutArchive &archive, unsigned int version) constshark::ISerializableinline
setLayer(std::size_t layerNumber, RealMatrix const &m, RealVector const &bias)shark::FFNet< HiddenNeuron, OutputNeuron >inline
setParameterVector(RealVector const &newParameters)shark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
setStructure(std::vector< size_t > const &layers, FFNetStructures::ConnectionType connectivity=FFNetStructures::Normal, bool biasNeuron=true)shark::FFNet< HiddenNeuron, OutputNeuron >inline
setStructure(std::size_t in, std::size_t hidden, std::size_t out, FFNetStructures::ConnectionType connectivity=FFNetStructures::Normal, bool bias=true)shark::FFNet< HiddenNeuron, OutputNeuron >inline
setStructure(std::size_t in, std::size_t hidden1, std::size_t hidden2, std::size_t out, FFNetStructures::ConnectionType connectivity=FFNetStructures::Normal, bool bias=true)shark::FFNet< HiddenNeuron, OutputNeuron >inline
updateFeatures()shark::AbstractModel< RealVector, RealVector >inlinevirtual
weightedDerivatives(BatchInputType const &patterns, BatchOutputType const &coefficients, State const &state, RealVector &parameterDerivative, BatchInputType &inputDerivative) constshark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
weightedInputDerivative(BatchInputType const &patterns, RealMatrix const &coefficients, State const &state, BatchInputType &inputDerivative) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
AbstractModel< RealVector, RealVector >::weightedInputDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, BatchInputType &derivative) constshark::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) constshark::AbstractModel< RealVector, RealVector >inlinevirtual
weightedParameterDerivative(BatchInputType const &patterns, RealMatrix const &coefficients, State const &state, RealVector &gradient) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
AbstractModel< RealVector, RealVector >::weightedParameterDerivative(BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, RealVector &derivative) constshark::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) constshark::AbstractModel< RealVector, RealVector >inlinevirtual
weightedParameterDerivativeFullDelta(RealMatrix const &patterns, RealMatrix &delta, State const &state, RealVector &gradient) constshark::FFNet< HiddenNeuron, OutputNeuron >inline
write(OutArchive &archive) constshark::FFNet< HiddenNeuron, OutputNeuron >inlinevirtual
~AbstractModel()shark::AbstractModel< RealVector, RealVector >inlinevirtual
~INameable()shark::INameableinlinevirtual
~IParameterizable()shark::IParameterizableinlinevirtual
~ISerializable()shark::ISerializableinlinevirtual