Linear Kernel, parameter free. More...
#include <shark/Models/Kernels/LinearKernel.h>
 Inheritance diagram for shark::LinearKernel< InputType >:
 Inheritance diagram for shark::LinearKernel< InputType >:| Public Member Functions | |
| LinearKernel () | |
| std::string | name () const | 
| From INameable: return the class name. | |
| RealVector | parameterVector () const | 
| Return the parameter vector. | |
| void | setParameterVector (RealVector const &newParameters) | 
| Set the parameter vector. | |
| boost::shared_ptr< State > | createState () const | 
| Creates an internal state of the kernel. | |
| double | eval (ConstInputReference x1, ConstInputReference x2) const | 
| void | eval (ConstBatchInputReference x1, ConstBatchInputReference x2, RealMatrix &result, State &state) const | 
| void | eval (ConstBatchInputReference x1, ConstBatchInputReference x2, RealMatrix &result) const | 
| void | weightedParameterDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficients, State const &state, RealVector &gradient) const | 
| void | weightedInputDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficientsX2, State const &state, BatchInputType &gradient) const | 
| virtual double | featureDistanceSqr (ConstInputReference x1, ConstInputReference x2) const | 
| virtual RealMatrix | featureDistanceSqr (ConstBatchInputReference x1, ConstBatchInputReference x2) const | 
| void | read (InArchive &ar) | 
| The kernel does not serialize anything. | |
| void | write (OutArchive &ar) const | 
| The kernel does not serialize anything. | |
|  Public Member Functions inherited from shark::AbstractKernelFunction< InputTypeT > | |
| AbstractKernelFunction () | |
| const Features & | features () const | 
| virtual void | updateFeatures () | 
| bool | hasFirstParameterDerivative () const | 
| bool | hasFirstInputDerivative () const | 
| bool | isNormalized () const | 
| bool | supportsVariableInputSize () const | 
| virtual double | eval (ConstInputReference x1, ConstInputReference x2) const | 
| Evaluates the kernel function. | |
| double | operator() (ConstInputReference x1, ConstInputReference x2) const | 
| Convenience operator which evaluates the kernel function. | |
| virtual void | eval (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result, State &state) const =0 | 
| Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns). | |
| virtual void | eval (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix &result) const | 
| Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns). | |
| RealMatrix | operator() (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2) const | 
| Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns). | |
| virtual void | weightedParameterDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficients, State const &state, RealVector &gradient) const | 
| Computes the gradient of the parameters as a weighted sum over the gradient of all elements of the batch. | |
| virtual void | weightedInputDerivative (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2, RealMatrix const &coefficientsX2, State const &state, BatchInputType &gradient) const | 
| Calculates the derivative of the inputs X1 (only x1!). | |
| virtual double | featureDistanceSqr (ConstInputReference x1, ConstInputReference x2) const | 
| Computes the squared distance in the kernel induced feature space. | |
| virtual RealMatrix | featureDistanceSqr (ConstBatchInputReference batchX1, ConstBatchInputReference batchX2) const | 
| Computes the squared distance in the kernel induced feature space. | |
|  Public Member Functions inherited from shark::AbstractMetric< InputTypeT > | |
| AbstractMetric () | |
| virtual | ~AbstractMetric () | 
| double | featureDistance (ConstInputReference x1, ConstInputReference x2) const | 
| Computes the distance in the kernel induced feature space. | |
|  Public Member Functions inherited from shark::INameable | |
| virtual | ~INameable () | 
|  Public Member Functions inherited from shark::IParameterizable< VectorType > | |
| virtual | ~IParameterizable () | 
| virtual std::size_t | numberOfParameters () const | 
| Return the number of parameters. | |
|  Public Member Functions inherited from shark::ISerializable | |
| virtual | ~ISerializable () | 
| Virtual d'tor. | |
| void | load (InArchive &archive, unsigned int version) | 
| Versioned loading of components, calls read(...). | |
| void | save (OutArchive &archive, unsigned int version) const | 
| Versioned storing of components, calls write(...). | |
| BOOST_SERIALIZATION_SPLIT_MEMBER () | |
| Additional Inherited Members | |
|  Protected Attributes inherited from shark::AbstractKernelFunction< InputTypeT > | |
| Features | m_features | 
Linear Kernel, parameter free.
Definition at line 47 of file LinearKernel.h.
| typedef base_type::BatchInputType shark::LinearKernel< InputType >::BatchInputType | 
Definition at line 52 of file LinearKernel.h.
| typedef base_type::ConstBatchInputReference shark::LinearKernel< InputType >::ConstBatchInputReference | 
Definition at line 54 of file LinearKernel.h.
| typedef base_type::ConstInputReference shark::LinearKernel< InputType >::ConstInputReference | 
Definition at line 53 of file LinearKernel.h.
| 
 | inline | 
Definition at line 56 of file LinearKernel.h.
References shark::AbstractKernelFunction< InputType >::HAS_FIRST_INPUT_DERIVATIVE, shark::AbstractKernelFunction< InputType >::HAS_FIRST_PARAMETER_DERIVATIVE, shark::AbstractKernelFunction< InputTypeT >::m_features, and shark::AbstractKernelFunction< InputType >::SUPPORTS_VARIABLE_INPUT_SIZE.
| 
 | inlinevirtual | 
Creates an internal state of the kernel.
The state is needed when the derivatives are to be calculated. Eval can store a state which is then reused to speed up the calculations of the derivatives. This also allows eval to be evaluated in parallel!
Reimplemented from shark::AbstractKernelFunction< InputTypeT >.
Definition at line 73 of file LinearKernel.h.
| 
 | inline | 
Definition at line 86 of file LinearKernel.h.
References SIZE_CHECK.
| 
 | inline | 
Definition at line 82 of file LinearKernel.h.
References shark::LinearKernel< InputType >::eval().
| 
 | inline | 
Definition at line 77 of file LinearKernel.h.
References SIZE_CHECK.
Referenced by shark::LinearKernel< InputType >::eval().
| 
 | inlinevirtual | 
Definition at line 121 of file LinearKernel.h.
| 
 | inlinevirtual | 
Definition at line 117 of file LinearKernel.h.
| 
 | inlinevirtual | 
From INameable: return the class name.
Reimplemented from shark::INameable.
Definition at line 63 of file LinearKernel.h.
| 
 | inlinevirtual | 
Return the parameter vector.
Reimplemented from shark::IParameterizable< VectorType >.
Definition at line 66 of file LinearKernel.h.
| 
 | inlinevirtual | 
The kernel does not serialize anything.
Reimplemented from shark::AbstractMetric< InputTypeT >.
Definition at line 126 of file LinearKernel.h.
| 
 | inlinevirtual | 
Set the parameter vector.
Reimplemented from shark::IParameterizable< VectorType >.
Definition at line 69 of file LinearKernel.h.
References SIZE_CHECK.
| 
 | inline | 
Definition at line 102 of file LinearKernel.h.
References SIZE_CHECK.
| 
 | inline | 
Definition at line 92 of file LinearKernel.h.
References SIZE_CHECK.
| 
 | inlinevirtual | 
The kernel does not serialize anything.
Reimplemented from shark::AbstractMetric< InputTypeT >.
Definition at line 129 of file LinearKernel.h.