Leave-one-out error objective function. More...
#include <shark/ObjectiveFunctions/LooError.h>
Inheritance diagram for shark::LooError< ModelTypeT, LabelType >:
Public Types | |
| typedef ModelTypeT | ModelType |
| typedef ModelType::InputType | InputType |
| typedef ModelType::OutputType | OutputType |
| typedef LabeledData< InputType, LabelType > | DatasetType |
| typedef AbstractTrainer< ModelType, LabelType > | TrainerType |
| typedef AbstractLoss< LabelType, typename ModelType::OutputType > | LossType |
| 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 | |
| LooError (DatasetType const &dataset, ModelType *model, TrainerType *trainer, LossType *loss, IParameterizable<> *meta=NULL) | |
| Constructor. More... | |
| std::string | name () const |
| From INameable: return the class name. More... | |
| std::size_t | numberOfVariables () const |
| Accesses the number of variables. More... | |
| double | eval () const |
| double | eval (const RealVector ¶meters) 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 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... | |
| ResultType | operator() (SearchPointType const &input) const |
| Evaluates the function. Useful together with STL-Algorithms like std::transform. More... | |
| virtual ResultType | evalDerivative (SearchPointType const &input, FirstOrderDerivative &derivative) const |
| Evaluates the objective function and calculates its gradient. More... | |
| virtual ResultType | evalDerivative (SearchPointType const &input, SecondOrderDerivative &derivative) const |
| Evaluates the objective function and calculates its gradient. More... | |
| Public Member Functions inherited from shark::INameable | |
| virtual | ~INameable () |
Protected Attributes | |
| DataView< DatasetType const > | m_dataset |
| IParameterizable * | mep_meta |
| ModelType * | mep_model |
| TrainerType * | mep_trainer |
| LossType * | mep_loss |
| 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 |
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... | |
Detailed Description
template<class ModelTypeT, class LabelType = typename ModelTypeT::OutputType>
class shark::LooError< ModelTypeT, LabelType >
Leave-one-out error objective function.
- The leave-one-out measure is the average prediction performance of a learning machine on a dataset, where each sample is predicted by a machine trained on all but the sample to be predicted. This is an extreme form of cross-validation, with a fold size of one.
- In general the leave-one-out error is costly to compute, since it requires training of a large number of learning machines. However, certain machines allow for a more efficient implementation. Refer to LooErrorCSvm for an example.
Definition at line 63 of file LooError.h.
Member Typedef Documentation
◆ DatasetType
| typedef LabeledData<InputType, LabelType> shark::LooError< ModelTypeT, LabelType >::DatasetType |
Definition at line 69 of file LooError.h.
◆ InputType
| typedef ModelType::InputType shark::LooError< ModelTypeT, LabelType >::InputType |
Definition at line 67 of file LooError.h.
◆ LossType
| typedef AbstractLoss<LabelType, typename ModelType::OutputType> shark::LooError< ModelTypeT, LabelType >::LossType |
Definition at line 71 of file LooError.h.
◆ ModelType
| typedef ModelTypeT shark::LooError< ModelTypeT, LabelType >::ModelType |
Definition at line 66 of file LooError.h.
◆ OutputType
| typedef ModelType::OutputType shark::LooError< ModelTypeT, LabelType >::OutputType |
Definition at line 68 of file LooError.h.
◆ TrainerType
| typedef AbstractTrainer<ModelType, LabelType> shark::LooError< ModelTypeT, LabelType >::TrainerType |
Definition at line 70 of file LooError.h.
Constructor & Destructor Documentation
◆ LooError()
|
inline |
Constructor.
- Parameters
-
dataset Full data set for leave-one-out. model Model built on subsets of the data. trainer Trainer for learning on each subset. loss Loss function for judging the validation output. meta Meta object with parameters that influences the process, typically a trainer.
Definition at line 82 of file LooError.h.
References shark::AbstractObjectiveFunction< RealVector, double >::HAS_VALUE, and shark::AbstractObjectiveFunction< RealVector, double >::m_features.
Member Function Documentation
◆ eval() [1/2]
|
inline |
Evaluate the leave-one-out error: train sub-models, evaluate objective, return the average.
Definition at line 114 of file LooError.h.
References shark::LooError< ModelTypeT, LabelType >::m_dataset, and shark::AbstractObjectiveFunction< RealVector, double >::m_evaluationCounter.
Referenced by shark::LooError< ModelTypeT, LabelType >::eval().
◆ eval() [2/2]
|
inlinevirtual |
Evaluate the leave-one-out error for the given parameters passed to the meta object (typically these parameters need to be optimized in a model selection procedure).
Reimplemented from shark::AbstractObjectiveFunction< RealVector, double >.
Definition at line 138 of file LooError.h.
References shark::LooError< ModelTypeT, LabelType >::eval(), shark::LooError< ModelTypeT, LabelType >::mep_meta, shark::IParameterizable< VectorType >::setParameterVector(), and SHARK_ASSERT.
◆ name()
|
inlinevirtual |
From INameable: return the class name.
Reimplemented from shark::INameable.
Definition at line 99 of file LooError.h.
References shark::LooError< ModelTypeT, LabelType >::mep_loss, shark::LooError< ModelTypeT, LabelType >::mep_model, shark::LooError< ModelTypeT, LabelType >::mep_trainer, and shark::INameable::name().
◆ numberOfVariables()
|
inlinevirtual |
Accesses the number of variables.
Implements shark::AbstractObjectiveFunction< RealVector, double >.
Definition at line 107 of file LooError.h.
References shark::LooError< ModelTypeT, LabelType >::mep_meta, and shark::IParameterizable< VectorType >::numberOfParameters().
Member Data Documentation
◆ m_dataset
|
protected |
Definition at line 144 of file LooError.h.
Referenced by shark::LooError< ModelTypeT, LabelType >::eval().
◆ mep_loss
|
protected |
Definition at line 148 of file LooError.h.
Referenced by shark::LooError< ModelTypeT, LabelType >::name().
◆ mep_meta
|
protected |
Definition at line 145 of file LooError.h.
Referenced by shark::LooError< ModelTypeT, LabelType >::eval(), and shark::LooError< ModelTypeT, LabelType >::numberOfVariables().
◆ mep_model
|
protected |
Definition at line 146 of file LooError.h.
Referenced by shark::LooError< ModelTypeT, LabelType >::name().
◆ mep_trainer
|
protected |
Definition at line 147 of file LooError.h.
Referenced by shark::LooError< ModelTypeT, LabelType >::name().
The documentation for this class was generated from the following file:
- include/shark/ObjectiveFunctions/LooError.h