Linear classifier in a kernel feature space. More...
#include <shark/Models/Kernels/KernelExpansion.h>
Public Member Functions | |
KernelClassifier () | |
KernelClassifier (KernelType *kernel) | |
KernelClassifier (KernelExpansionType const &decisionFunction) | |
std::string | name () const |
returns the name of the object More... | |
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ArgMaxConverter () | |
ArgMaxConverter (KernelExpansion< InputType > const &decisionFunction) | |
std::string | name () const |
returns the name of the object More... | |
RealVector | parameterVector () const |
Return the parameter vector. More... | |
void | setParameterVector (RealVector const &newParameters) |
Set the parameter vector. More... | |
std::size_t | numberOfParameters () const |
Return the number of parameters. More... | |
KernelExpansion< InputType > const & | decisionFunction () const |
Return the decision function. More... | |
KernelExpansion< InputType > & | decisionFunction () |
Return the decision function. More... | |
void | eval (BatchInputType const &input, BatchOutputType &output) const |
void | eval (BatchInputType const &input, BatchOutputType &output, State &state) const |
void | eval (InputType const &pattern, OutputType &output) const |
Standard interface for evaluating the response of the model to a single pattern. More... | |
void | read (InArchive &archive) |
From ISerializable. More... | |
void | write (OutArchive &archive) const |
From ISerializable. More... | |
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AbstractModel () | |
virtual | ~AbstractModel () |
const Features & | features () const |
virtual void | updateFeatures () |
bool | hasFirstParameterDerivative () const |
Returns true when the first parameter derivative is implemented. More... | |
bool | hasSecondParameterDerivative () const |
Returns true when the second parameter derivative is implemented. More... | |
bool | hasFirstInputDerivative () const |
Returns true when the first input derivative is implemented. More... | |
bool | hasSecondInputDerivative () const |
Returns true when the second parameter derivative is implemented. More... | |
bool | isSequential () const |
virtual boost::shared_ptr< State > | createState () const |
Creates an internal state of the model. More... | |
Data< OutputType > | operator() (Data< InputType > const &patterns) const |
Model evaluation as an operator for a whole dataset. This is a convenience function. More... | |
OutputType | operator() (InputType const &pattern) const |
Model evaluation as an operator for a single pattern. This is a convenience function. More... | |
BatchOutputType | operator() (BatchInputType const &patterns) const |
Model evaluation as an operator for a single pattern. This is a convenience function. More... | |
virtual void | weightedParameterDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, RealVector &derivative) const |
calculates the weighted sum of derivatives w.r.t the parameters. More... | |
virtual void | weightedParameterDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, Batch< RealMatrix >::type const &errorHessian, State const &state, RealVector &derivative, RealMatrix &hessian) const |
calculates the weighted sum of derivatives w.r.t the parameters More... | |
virtual void | weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, BatchInputType &derivative) const |
calculates the weighted sum of derivatives w.r.t the inputs More... | |
virtual void | weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, typename Batch< RealMatrix >::type const &errorHessian, State const &state, RealMatrix &derivative, Batch< RealMatrix >::type &hessian) const |
calculates the weighted sum of derivatives w.r.t the inputs More... | |
virtual void | weightedDerivatives (BatchInputType const &patterns, BatchOutputType const &coefficients, State const &state, RealVector ¶meterDerivative, BatchInputType &inputDerivative) const |
calculates weighted input and parameter derivative at the same time More... | |
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virtual | ~IParameterizable () |
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virtual | ~INameable () |
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virtual | ~ISerializable () |
Virtual d'tor. More... | |
void | load (InArchive &archive, unsigned int version) |
Versioned loading of components, calls read(...). More... | |
void | save (OutArchive &archive, unsigned int version) const |
Versioned storing of components, calls write(...). More... | |
BOOST_SERIALIZATION_SPLIT_MEMBER () | |
Additional Inherited Members | |
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Features | m_features |
Linear classifier in a kernel feature space.
This model is a simple wrapper for the KernelExpansion calculating the arg max of the outputs of the model. This is the model used by kernel classifier models like SVMs.
Definition at line 312 of file KernelExpansion.h.
typedef KernelExpansion<InputType> shark::KernelClassifier< InputType >::KernelExpansionType |
Definition at line 315 of file KernelExpansion.h.
typedef AbstractKernelFunction<InputType> shark::KernelClassifier< InputType >::KernelType |
Definition at line 314 of file KernelExpansion.h.
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inline |
Definition at line 317 of file KernelExpansion.h.
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inline |
Definition at line 319 of file KernelExpansion.h.
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inline |
Definition at line 322 of file KernelExpansion.h.
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inlinevirtual |
returns the name of the object
Reimplemented from shark::INameable.
Definition at line 326 of file KernelExpansion.h.
Referenced by main().