shark::LinearClassifier< VectorType > Class Template Reference
Basic linear classifier. More...
#include <shark/Models/LinearClassifier.h>
Inheritance diagram for shark::LinearClassifier< VectorType >:
Public Member Functions | |
| LinearClassifier () | |
| std::string | name () const |
| returns the name of the object More... | |
| Public Member Functions inherited from shark::ArgMaxConverter< LinearModel< VectorType > > | |
| ArgMaxConverter () | |
| ArgMaxConverter (LinearModel< VectorType > 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... | |
| LinearModel< VectorType > const & | decisionFunction () const |
| Return the decision function. More... | |
| LinearModel< VectorType > & | 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... | |
| Public Member Functions inherited from shark::AbstractModel< LinearModel< VectorType > ::InputType, unsigned int > | |
| 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... | |
| Public Member Functions inherited from shark::IParameterizable | |
| virtual | ~IParameterizable () |
| Public Member Functions inherited from shark::INameable | |
| virtual | ~INameable () |
| Public Member Functions inherited from shark::ISerializable | |
| 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 () | |
Detailed Description
template<class VectorType = RealVector>
class shark::LinearClassifier< VectorType >
Basic linear classifier.
The LinearClassifier class is a multi class classifier model suited for linear discriminant analysis. For c classes \( 0, \dots, c-1 \) the model computes
\( \arg \max_i w_i^T x + b_i \)
Thus is it a linear model with arg max computation. The internal linear model can be queried using decisionFunction().
Definition at line 47 of file LinearClassifier.h.
Constructor & Destructor Documentation
§ LinearClassifier()
template<class VectorType = RealVector>
|
inline |
Definition at line 50 of file LinearClassifier.h.
Member Function Documentation
§ name()
template<class VectorType = RealVector>
|
inlinevirtual |
returns the name of the object
Reimplemented from shark::INameable.
Definition at line 52 of file LinearClassifier.h.
The documentation for this class was generated from the following file:
- include/shark/Models/LinearClassifier.h