shark::ErrorFunction Class Reference

Objective function for supervised learning. More...

#include <shark/ObjectiveFunctions/ErrorFunction.h>

+ Inheritance diagram for shark::ErrorFunction:

Public Member Functions

template<class InputType , class LabelType , class OutputType >
 ErrorFunction (LabeledData< InputType, LabelType > const &dataset, AbstractModel< InputType, OutputType > *model, AbstractLoss< LabelType, OutputType > *loss)
 
 ErrorFunction (const ErrorFunction &op)
 
ErrorFunctionoperator= (const ErrorFunction &op)
 
std::string name () const
 returns the name of the object More...
 
void setRegularizer (double factor, SingleObjectiveFunction *regularizer)
 
SearchPointType proposeStartingPoint () const
 Proposes a starting point in the feasible search space of the function. More...
 
std::size_t numberOfVariables () const
 Accesses the number of variables. More...
 
double eval (RealVector const &input) const
 Evaluates the objective function for the supplied argument. More...
 
ResultType evalDerivative (const SearchPointType &input, FirstOrderDerivative &derivative) const
 Evaluates the objective function and calculates its gradient. More...
 
- Public Member Functions inherited from shark::AbstractObjectiveFunction< RealVector, double >
const Featuresfeatures () 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...
 
 AbstractObjectiveFunction ()
 Default ctor. More...
 
virtual ~AbstractObjectiveFunction ()
 Virtual destructor. More...
 
virtual void init ()
 
virtual bool hasScalableDimensionality () const
 
virtual void setNumberOfVariables (std::size_t numberOfVariables)
 Adjusts the number of variables if the function is scalable. 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...
 
ResultType operator() (const SearchPointType &input) const
 Evaluates the function. Useful together with STL-Algorithms like std::transform. More...
 
virtual ResultType evalDerivative (const SearchPointType &input, SecondOrderDerivative &derivative) const
 Evaluates the objective function and calculates its gradient. More...
 
- Public Member Functions inherited from shark::INameable
virtual ~INameable ()
 

Friends

void swap (ErrorFunction &op1, ErrorFunction &op2)
 

Additional Inherited Members

- 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 SearchPointType FirstOrderDerivative
 
typedef TypedFlags< FeatureFeatures
 This statement declares the member m_features. See Core/Flags.h for details. More...
 
typedef TypedFeatureNotAvailableException< FeatureFeatureNotAvailableException
 
- 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
 

Detailed Description

Objective function for supervised learning.

An ErrorFunction object is an objective function for learning the parameters of a model from data by means of minimization of a cost function. The value of the objective function is the cost of the model predictions on the training data, given the targets.
The class detects automatically when an AbstractLoss is used as Costfunction. In this case, it uses faster algorithms for empirical risk minimization
It also automatically infers the input und label type from the given dataset and the output type of the model in the constructor and ensures that Model and loss match. Thus the user does not need to provide the types as template parameters.

Definition at line 65 of file ErrorFunction.h.

Constructor & Destructor Documentation

§ ErrorFunction() [1/2]

template<class InputType , class LabelType , class OutputType >
shark::ErrorFunction::ErrorFunction ( LabeledData< InputType, LabelType > const &  dataset,
AbstractModel< InputType, OutputType > *  model,
AbstractLoss< LabelType, OutputType > *  loss 
)

§ ErrorFunction() [2/2]

shark::ErrorFunction::ErrorFunction ( const ErrorFunction op)

Member Function Documentation

§ eval()

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

Evaluates the objective function for the supplied argument.

Parameters
[in]inputThe argument for which the function shall be evaluated.
Returns
The result of evaluating the function for the supplied argument.
Exceptions
FeatureNotAvailableExceptionin the default implementation and if a function does not support this feature.

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

Referenced by numberOfVariables().

§ evalDerivative()

ResultType shark::ErrorFunction::evalDerivative ( const SearchPointType input,
FirstOrderDerivative derivative 
) const
virtual

Evaluates the objective function and calculates its gradient.

Parameters
[in]inputThe argument to eval the function for.
[out]derivativeThe derivate is placed here.
Returns
The result of evaluating the function for the supplied argument.
Exceptions
FeatureNotAvailableExceptionin the default implementation and if a function does not support this feature.

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

Referenced by numberOfVariables().

§ name()

std::string shark::ErrorFunction::name ( ) const
inlinevirtual

returns the name of the object

Reimplemented from shark::INameable.

Definition at line 78 of file ErrorFunction.h.

§ numberOfVariables()

std::size_t shark::ErrorFunction::numberOfVariables ( ) const
inlinevirtual

Accesses the number of variables.

Implements shark::AbstractObjectiveFunction< RealVector, double >.

Definition at line 89 of file ErrorFunction.h.

References eval(), evalDerivative(), and swap.

Referenced by main(), and trainAutoencoderModel().

§ operator=()

ErrorFunction& shark::ErrorFunction::operator= ( const ErrorFunction op)

§ proposeStartingPoint()

SearchPointType shark::ErrorFunction::proposeStartingPoint ( ) const
inlinevirtual

Proposes a starting point in the feasible search space of the function.

Returns
The generated starting point.
Exceptions
FeatureNotAvailableExceptionin the default implementation and if a function does not support this feature.

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

Definition at line 86 of file ErrorFunction.h.

§ setRegularizer()

void shark::ErrorFunction::setRegularizer ( double  factor,
SingleObjectiveFunction regularizer 
)
inline

Definition at line 81 of file ErrorFunction.h.

Referenced by main(), and trainAutoencoderModel().

Friends And Related Function Documentation

§ swap

void swap ( ErrorFunction op1,
ErrorFunction op2 
)
friend

Referenced by numberOfVariables().


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