| AbstractKernelFunction() | shark::AbstractKernelFunction< std::size_t > | inline |
| AbstractMetric() | shark::AbstractMetric< std::size_t > | inline |
| BatchInputType typedef | shark::AbstractKernelFunction< std::size_t > | |
| BOOST_SERIALIZATION_SPLIT_MEMBER() | shark::ISerializable | |
| computeMatrix() | shark::GaussianTaskKernel< InputTypeT > | inlineprotected |
| ConstBatchInputReference typedef | shark::AbstractKernelFunction< std::size_t > | |
| ConstInputReference typedef | shark::AbstractKernelFunction< std::size_t > | |
| createState() const | shark::DiscreteKernel | inlinevirtual |
| DiscreteKernel(RealMatrix const &matrix) | shark::DiscreteKernel | inline |
| eval(ConstInputReference x1, ConstInputReference x2) const | shark::DiscreteKernel | inlinevirtual |
| eval(ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result, State &state) const | shark::DiscreteKernel | inlinevirtual |
| eval(ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result) const | shark::DiscreteKernel | inlinevirtual |
| Feature enum name | shark::AbstractKernelFunction< std::size_t > | |
| featureDistance(ConstInputReference x1, ConstInputReference x2) const | shark::AbstractMetric< std::size_t > | inline |
| featureDistanceSqr(ConstInputReference x1, ConstInputReference x2) const | shark::AbstractKernelFunction< std::size_t > | inlinevirtual |
| featureDistanceSqr(ConstBatchInputReference batchX1, ConstBatchInputReference batchX2) const | shark::AbstractKernelFunction< std::size_t > | inlinevirtual |
| AbstractMetric< std::size_t >::featureDistanceSqr(ConstInputReference x1, ConstInputReference x2) const=0 | shark::AbstractMetric< std::size_t > | pure virtual |
| FeatureNotAvailableException typedef | shark::AbstractKernelFunction< std::size_t > | |
| features() const | shark::AbstractKernelFunction< std::size_t > | inline |
| Features typedef | shark::AbstractKernelFunction< std::size_t > | |
| gamma() const | shark::GaussianTaskKernel< InputTypeT > | inline |
| GaussianTaskKernel(Data< MultiTaskSampleType > const &data, std::size_t tasks, KernelType &inputkernel, double gamma) | shark::GaussianTaskKernel< InputTypeT > | inline |
| HAS_FIRST_INPUT_DERIVATIVE enum value | shark::AbstractKernelFunction< std::size_t > | |
| HAS_FIRST_PARAMETER_DERIVATIVE enum value | shark::AbstractKernelFunction< std::size_t > | |
| hasFirstInputDerivative() const | shark::AbstractKernelFunction< std::size_t > | inline |
| hasFirstParameterDerivative() const | shark::AbstractKernelFunction< std::size_t > | inline |
| InputType typedef | shark::GaussianTaskKernel< InputTypeT > | |
| IS_NORMALIZED enum value | shark::AbstractKernelFunction< std::size_t > | |
| isNormalized() const | shark::AbstractKernelFunction< std::size_t > | inline |
| KernelType typedef | shark::GaussianTaskKernel< InputTypeT > | |
| load(InArchive &archive, unsigned int version) | shark::ISerializable | inline |
| m_data | shark::GaussianTaskKernel< InputTypeT > | protected |
| m_features | shark::AbstractKernelFunction< std::size_t > | protected |
| m_gamma | shark::GaussianTaskKernel< InputTypeT > | protected |
| m_matrix | shark::DiscreteKernel | protected |
| mpe_inputKernel | shark::GaussianTaskKernel< InputTypeT > | protected |
| MultiTaskSampleType typedef | shark::GaussianTaskKernel< InputTypeT > | |
| name() const | shark::GaussianTaskKernel< InputTypeT > | inlinevirtual |
| numberOfParameters() const | shark::GaussianTaskKernel< InputTypeT > | inlinevirtual |
| numberOfTasks() const | shark::GaussianTaskKernel< InputTypeT > | inline |
| operator()(ConstInputReference x1, ConstInputReference x2) const | shark::AbstractKernelFunction< std::size_t > | inline |
| operator()(ConstBatchInputReference batchX1, ConstBatchInputReference batchX2) const | shark::AbstractKernelFunction< std::size_t > | inline |
| parameterVector() const | shark::GaussianTaskKernel< InputTypeT > | inlinevirtual |
| ParameterVectorType typedef | shark::IParameterizable<> | |
| read(InArchive &ar) | shark::GaussianTaskKernel< InputTypeT > | inlinevirtual |
| save(OutArchive &archive, unsigned int version) const | shark::ISerializable | inline |
| setGamma(double gamma) | shark::GaussianTaskKernel< InputTypeT > | inline |
| setParameterVector(RealVector const &newParameters) | shark::GaussianTaskKernel< InputTypeT > | inlinevirtual |
| setWidth(double sigma) | shark::GaussianTaskKernel< InputTypeT > | inline |
| sigma() const | shark::GaussianTaskKernel< InputTypeT > | inline |
| size() const | shark::DiscreteKernel | inline |
| SUPPORTS_VARIABLE_INPUT_SIZE enum value | shark::AbstractKernelFunction< std::size_t > | |
| supportsVariableInputSize() const | shark::AbstractKernelFunction< std::size_t > | inline |
| updateFeatures() | shark::AbstractKernelFunction< std::size_t > | inlinevirtual |
| weightedInputDerivative(ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficientsX2, State const &state, BatchInputType &gradient) const | shark::AbstractKernelFunction< std::size_t > | inlinevirtual |
| weightedParameterDerivative(ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficients, State const &state, RealVector &gradient) const | shark::AbstractKernelFunction< std::size_t > | inlinevirtual |
| write(OutArchive &ar) const | shark::GaussianTaskKernel< InputTypeT > | inlinevirtual |
| ~AbstractMetric() | shark::AbstractMetric< std::size_t > | inlinevirtual |
| ~INameable() | shark::INameable | inlinevirtual |
| ~IParameterizable() | shark::IParameterizable<> | inlinevirtual |
| ~ISerializable() | shark::ISerializable | inlinevirtual |