Two-norm of the input as an objective function. More...

#include <shark/ObjectiveFunctions/Regularizer.h>

Inheritance diagram for shark::TwoNormRegularizer:

Public Types
typedef RealVector	SearchPointType

typedef double	ResultType

typedef AbstractObjectiveFunction< RealVector, double >	super

Public Types inherited from shark::AbstractObjectiveFunction< RealVector, double >
enum	Feature
	List of features that are supported by an implementation. More...

typedef RealVector	SearchPointType

typedef double	ResultType

typedef boost::mpl::if_< std::is_arithmetic< double >, SearchPointType, RealMatrix >::type	FirstOrderDerivative

typedef TypedFlags< Feature >	Features
	This statement declares the member m_features. See Core/Flags.h for details. More...

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Public Member Functions
	TwoNormRegularizer (std::size_t numVariables=0)
	Constructor. More...

std::string	name () const
	From INameable: return the class name. More...

std::size_t	numberOfVariables () const
	Accesses the number of variables. More...

bool	hasScalableDimensionality () const

void	setNumberOfVariables (std::size_t numberOfVariables)
	Adjusts the number of variables if the function is scalable. More...

void	setMask (const RealVector &mask)

const RealVector &	mask () const

virtual double	eval (RealVector const &input) const
	Evaluates the objective function. More...

virtual double	evalDerivative (RealVector const &input, FirstOrderDerivative &derivative) const

virtual ResultType	evalDerivative (const SearchPointType &input, SecondOrderDerivative &derivative) const

Public Member Functions inherited from shark::AbstractObjectiveFunction< RealVector, double >
const Features &	features () const

virtual void	updateFeatures ()

bool	hasValue () const
	returns whether this function can calculate it's function value More...

bool	hasFirstDerivative () const
	returns whether this function can calculate the first derivative More...

bool	hasSecondDerivative () const
	returns whether this function can calculate the second derivative More...

bool	canProposeStartingPoint () const
	returns whether this function can propose a starting point. More...

bool	isConstrained () const
	returns whether this function can return More...

bool	hasConstraintHandler () const
	returns whether this function can return More...

bool	canProvideClosestFeasible () const
	Returns whether this function can calculate thee closest feasible to an infeasible point. More...

bool	isThreadSafe () const
	Returns true, when the function can be usd in parallel threads. More...

bool	isNoisy () const
	Returns true, when the function can be usd in parallel threads. More...

	AbstractObjectiveFunction ()
	Default ctor. More...

virtual	~AbstractObjectiveFunction ()
	Virtual destructor. More...

virtual void	init ()

void	setRng (random::rng_type *rng)
	Sets the Rng used by the objective function. More...

virtual std::size_t	numberOfObjectives () const

virtual bool	hasScalableObjectives () const

virtual void	setNumberOfObjectives (std::size_t numberOfObjectives)
	Adjusts the number of objectives if the function is scalable. More...

std::size_t	evaluationCounter () const
	Accesses the evaluation counter of the function. More...

AbstractConstraintHandler< SearchPointType > const &	getConstraintHandler () const
	Returns the constraint handler of the function if it has one. More...

virtual bool	isFeasible (const SearchPointType &input) const
	Tests whether a point in SearchSpace is feasible, e.g., whether the constraints are fulfilled. More...

virtual void	closestFeasible (SearchPointType &input) const
	If supported, the supplied point is repaired such that it satisfies all of the function's constraints. More...

virtual SearchPointType	proposeStartingPoint () const
	Proposes a starting point in the feasible search space of the function. More...

ResultType	operator() (SearchPointType const &input) const
	Evaluates the function. Useful together with STL-Algorithms like std::transform. More...

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

Additional Inherited Members
Protected Member Functions inherited from shark::AbstractObjectiveFunction< RealVector, double >
void	announceConstraintHandler (AbstractConstraintHandler< SearchPointType > const *handler)
	helper function which is called to announce the presence of an constraint handler. More...

Protected Attributes inherited from shark::AbstractObjectiveFunction< RealVector, double >
Features	m_features

std::size_t	m_evaluationCounter
	Evaluation counter, default value: 0. More...

AbstractConstraintHandler< SearchPointType > const *	m_constraintHandler

random::rng_type *	mep_rng

Detailed Description

Two-norm of the input as an objective function.

: The TwoNormRegularizer is intended to be used together with other objective functions within a CombinedObjectiveFunction, in order to obtain a more smooth solution.

Definition at line 147 of file Regularizer.h.

Member Typedef Documentation

◆ ResultType

typedef double shark::TwoNormRegularizer::ResultType

Definition at line 151 of file Regularizer.h.

◆ SearchPointType

typedef RealVector shark::TwoNormRegularizer::SearchPointType

Definition at line 150 of file Regularizer.h.

◆ super

typedef AbstractObjectiveFunction<RealVector, double> shark::TwoNormRegularizer::super

Definition at line 153 of file Regularizer.h.

Constructor & Destructor Documentation

◆ TwoNormRegularizer()

shark::TwoNormRegularizer::TwoNormRegularizer ( std::size_t numVariables = 0 )

inline

Constructor.

Definition at line 156 of file Regularizer.h.

References shark::AbstractObjectiveFunction< RealVector, double >::HAS_FIRST_DERIVATIVE, shark::AbstractObjectiveFunction< RealVector, double >::HAS_SECOND_DERIVATIVE, and shark::AbstractObjectiveFunction< RealVector, double >::m_features.

Member Function Documentation

◆ eval()

virtual double shark::TwoNormRegularizer::eval ( RealVector const & input ) const

inlinevirtual

Evaluates the objective function.

Reimplemented from shark::AbstractObjectiveFunction< RealVector, double >.

Definition at line 186 of file Regularizer.h.

◆ evalDerivative() [1/2]

virtual double shark::TwoNormRegularizer::evalDerivative	(	RealVector const &	input,
		FirstOrderDerivative &	derivative
	)		const

inlinevirtual

Evaluates the objective function and calculates its gradient.

Reimplemented from shark::AbstractObjectiveFunction< RealVector, double >.

Definition at line 198 of file Regularizer.h.

References shark::OneNormRegularizer::eval().

◆ evalDerivative() [2/2]

virtual ResultType shark::TwoNormRegularizer::evalDerivative	(	const SearchPointType &	input,
		SecondOrderDerivative &	derivative
	)		const

inlinevirtual

Evaluates the objective function and calculates its gradient and its Hessian.

Reimplemented from shark::AbstractObjectiveFunction< RealVector, double >.

Definition at line 211 of file Regularizer.h.

◆ hasScalableDimensionality()

bool shark::TwoNormRegularizer::hasScalableDimensionality ( ) const

inlinevirtual

Reimplemented from shark::AbstractObjectiveFunction< RealVector, double >.

Definition at line 170 of file Regularizer.h.

◆ mask()

const RealVector& shark::TwoNormRegularizer::mask ( ) const

inline

Definition at line 181 of file Regularizer.h.

◆ name()

std::string shark::TwoNormRegularizer::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 163 of file Regularizer.h.

◆ numberOfVariables()

std::size_t shark::TwoNormRegularizer::numberOfVariables ( ) const

inlinevirtual

Accesses the number of variables.

Implements shark::AbstractObjectiveFunction< RealVector, double >.

Definition at line 166 of file Regularizer.h.

◆ setMask()

void shark::TwoNormRegularizer::setMask ( const RealVector & mask )

inline

Definition at line 178 of file Regularizer.h.

References shark::OneNormRegularizer::mask().

◆ setNumberOfVariables()

void shark::TwoNormRegularizer::setNumberOfVariables ( std::size_t numberOfVariables )

inlinevirtual

Adjusts the number of variables if the function is scalable.

Parameters

[in] numberOfVariables The new dimension.

Reimplemented from shark::AbstractObjectiveFunction< RealVector, double >.

Definition at line 174 of file Regularizer.h.

References shark::OneNormRegularizer::numberOfVariables().

The documentation for this class was generated from the following file:

include/shark/ObjectiveFunctions/Regularizer.h

Public Types

Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ ResultType

◆ SearchPointType

◆ super

Constructor & Destructor Documentation

◆ TwoNormRegularizer()

Member Function Documentation

◆ eval()

◆ evalDerivative() [1/2]

◆ evalDerivative() [2/2]

◆ hasScalableDimensionality()

◆ mask()

◆ name()

◆ numberOfVariables()

◆ setMask()

◆ setNumberOfVariables()