shark::CrossValidationError< ModelTypeT, LabelTypeT > Class Template Reference
Cross-validation error for selection of hyper-parameters. More...
#include <shark/ObjectiveFunctions/CrossValidationError.h>
Inheritance diagram for shark::CrossValidationError< ModelTypeT, LabelTypeT >:
Public Member Functions | |
| CrossValidationError (FoldsType const &dataFolds, IParameterizable *meta, ModelType *model, TrainerType *trainer, CostType *cost) | |
| std::string | name () const |
| From INameable: return the class name. More... | |
| std::size_t | numberOfVariables () const |
| Accesses the number of variables. More... | |
| double | eval (RealVector const ¶meters) const |
| Public Member Functions inherited from shark::AbstractObjectiveFunction< PointType, ResultT > | |
| 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... | |
| 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... | |
| virtual SearchPointType | proposeStartingPoint () const |
| Proposes a starting point in the feasible search space of the function. More... | |
| virtual ResultType | eval (const SearchPointType &input) const |
| Evaluates the objective function for the supplied argument. 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, FirstOrderDerivative &derivative) const |
| Evaluates the objective function and calculates its gradient. 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 () |
Additional Inherited Members | |
| Protected Member Functions inherited from shark::AbstractObjectiveFunction< PointType, ResultT > | |
| 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< PointType, ResultT > | |
| Features | m_features |
| std::size_t | m_evaluationCounter |
| Evaluation counter, default value: 0. More... | |
| AbstractConstraintHandler< SearchPointType > const * | m_constraintHandler |
Detailed Description
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
class shark::CrossValidationError< ModelTypeT, LabelTypeT >
Cross-validation error for selection of hyper-parameters.
- The cross-validation error is useful for evaluating how well a model performs on a problem. It is regularly used for model selection.
- In Shark, the cross-validation procedure is abstracted as follows: First, the given point is written into an IParameterizable object (such as a regularizer or a trainer). Then a model is trained with a trainer with the given settings on a number of folds and evaluated on the corresponding validation sets with a cost function. The average cost function value over all folds is returned.
- Thus, the cross-validation procedure requires a "meta" IParameterizable object, a model, a trainer, a data set, and a cost function.
Definition at line 72 of file CrossValidationError.h.
Member Typedef Documentation
§ CostType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef AbstractCost<LabelType, OutputType> shark::CrossValidationError< ModelTypeT, LabelTypeT >::CostType |
Definition at line 82 of file CrossValidationError.h.
§ DatasetType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef LabeledData<InputType, LabelType> shark::CrossValidationError< ModelTypeT, LabelTypeT >::DatasetType |
Definition at line 78 of file CrossValidationError.h.
§ FoldsType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef CVFolds<DatasetType> shark::CrossValidationError< ModelTypeT, LabelTypeT >::FoldsType |
Definition at line 79 of file CrossValidationError.h.
§ InputType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef ModelTypeT::InputType shark::CrossValidationError< ModelTypeT, LabelTypeT >::InputType |
Definition at line 75 of file CrossValidationError.h.
§ LabelType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef LabelTypeT shark::CrossValidationError< ModelTypeT, LabelTypeT >::LabelType |
Definition at line 77 of file CrossValidationError.h.
§ ModelType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef ModelTypeT shark::CrossValidationError< ModelTypeT, LabelTypeT >::ModelType |
Definition at line 80 of file CrossValidationError.h.
§ OutputType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef ModelTypeT::OutputType shark::CrossValidationError< ModelTypeT, LabelTypeT >::OutputType |
Definition at line 76 of file CrossValidationError.h.
§ TrainerType
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
| typedef AbstractTrainer<ModelType, LabelType> shark::CrossValidationError< ModelTypeT, LabelTypeT >::TrainerType |
Definition at line 81 of file CrossValidationError.h.
Constructor & Destructor Documentation
§ CrossValidationError()
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
|
inline |
Definition at line 95 of file CrossValidationError.h.
Member Function Documentation
§ eval()
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
|
inline |
Evaluate the cross-validation error: train sub-models, evaluate objective, return the average.
Definition at line 124 of file CrossValidationError.h.
References shark::AbstractCost< LabelT, OutputT >::eval(), shark::LabeledData< InputT, LabelT >::inputs(), shark::LabeledData< InputT, LabelT >::labels(), shark::AbstractObjectiveFunction< PointType, ResultT >::m_evaluationCounter, shark::IParameterizable::setParameterVector(), shark::CVFolds< DatasetTypeT >::size(), shark::AbstractTrainer< Model, LabelTypeT >::train(), shark::CVFolds< DatasetTypeT >::training(), and shark::CVFolds< DatasetTypeT >::validation().
§ name()
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
|
inlinevirtual |
From INameable: return the class name.
Reimplemented from shark::INameable.
Definition at line 109 of file CrossValidationError.h.
References shark::INameable::name().
§ numberOfVariables()
template<class ModelTypeT, class LabelTypeT = typename ModelTypeT::OutputType>
|
inlinevirtual |
Accesses the number of variables.
Implements shark::AbstractObjectiveFunction< PointType, ResultT >.
Definition at line 117 of file CrossValidationError.h.
References shark::IParameterizable::numberOfParameters().
The documentation for this class was generated from the following file:
- include/shark/ObjectiveFunctions/CrossValidationError.h