File learner_common.hpp

namespace seco

class SeCoRuleLearnerConfigurator : public RuleLearnerConfigurator

#include <learner_common.hpp>

Allows to configure the individual modules of a rule learner that makes use of the separate-and-conquer (SeCo) paradigm, depending on an ISeCoRuleLearnerConfig.

Public Functions

inline SeCoRuleLearnerConfigurator(std::unique_ptr<ISeCoRuleLearnerConfig> configPtr)

Parameters:

configPtr – An unique pointer to an object of type ISeCoRuleLearnerConfig

inline void createStoppingCriterionFactories(StoppingCriterionListFactory &factory) const override

See also

RuleLearnerConfigurator::createStoppingCriterionFactories

inline std::unique_ptr<IClassificationStatisticsProviderFactory> createClassificationStatisticsProviderFactory(const IFeatureMatrix &featureMatrix, const IRowWiseLabelMatrix &labelMatrix) const override

See also

RuleLearnerConfigurator::createClassificationStatisticsProviderFactory

inline std::unique_ptr<IRegressionStatisticsProviderFactory> createRegressionStatisticsProviderFactory(const IFeatureMatrix &featureMatrix, const IRowWiseRegressionMatrix &regressionMatrix) const override

See also

RuleLearnerConfigurator::createRegressionStatisticsProviderFactory

inline std::unique_ptr<IModelBuilderFactory> createModelBuilderFactory() const override

See also

RuleLearnerConfigurator::createModelBuilderFactory

inline std::unique_ptr<ISparseBinaryPredictorFactory> createSparseBinaryPredictorFactory(const IRowWiseFeatureMatrix &featureMatrix, uint32 numLabels) const override

See also

RuleLearnerConfigurator::createSparseBinaryPredictorFactory

Private Functions

inline std::unique_ptr<IStoppingCriterionFactory> createCoverageStoppingCriterionFactory() const

Private Members

std::unique_ptr<ISeCoRuleLearnerConfig> configPtr_

class SeCoRuleLearnerConfig : public RuleLearnerConfig, public virtual seco::ISeCoRuleLearnerConfig

#include <learner_common.hpp>

Allows to configure a rule learner that makes use of the separate-and-conquer (SeCo) paradigm.

Public Functions

inline SeCoRuleLearnerConfig()

inline virtual ~SeCoRuleLearnerConfig() override

inline virtual Property<IStoppingCriterionConfig> getCoverageStoppingCriterionConfig() final override

Returns a Property that allows to access the IStoppingCriterionConfig that stores the configuration of the stopping criterion that stops the induction of rules as soon as enough of the label space is covered.

Returns:

A Property that allows to access the IStoppingCriterionConfig that stores the configuration of the stopping criterion that stops the induction of rules as soon as enough of the label space is covered

inline virtual Property<IHeadConfig> getHeadConfig() final override

Returns a Property that allows to access the IHeadConfig that stores the configuration of the rule heads that should be induced by the rule learner.

Returns:

A Property that allows to access the IHeadConfig that stores the configuration of the rule heads that should be induced by the rule learner

inline virtual Property<IHeuristicConfig> getHeuristicConfig() final override

Returns a Property that allows to access the IHeuristicConfig that stores the configuration of the heuristic for learning rules.

Returns:

A Property that allows to access the IHeuristicConfig that stores the configuration of the heuristic for learning rules

inline virtual Property<IHeuristicConfig> getPruningHeuristicConfig() final override

Returns a Property that allows to access the IHeuristicConfig that stores the configuration of the heuristic for pruning rules.

Returns:

A Property that allows to access the IHeuristicConfig that stores the configuration of the heuristic for pruning rules

inline virtual Property<ILiftFunctionConfig> getLiftFunctionConfig() final override

Returns a Property that allows to access the ILiftFunctionConfig that stores the configuration of the lift function that affects the quality of rules, depending on the number of labels for which they predict.

Returns:

A Property that allows to access the ILiftFunctionConfig that stores the configuration of the lift function that affects the quality of rules, depending on the number of labels for which they predict

Protected Attributes

std::unique_ptr<IStoppingCriterionConfig> coverageStoppingCriterionConfigPtr_

An unique pointer that stores the configuration of the stopping criterion that stops the induction of rules as soon as enough of the label space is covered.

std::unique_ptr<IHeadConfig> headConfigPtr_

An unique pointer that stores the configuration of the rule heads.

std::unique_ptr<IHeuristicConfig> heuristicConfigPtr_

An unique pointer that stores the configuration of the heuristic that is used for learning rules.

std::unique_ptr<IHeuristicConfig> pruningHeuristicConfigPtr_

An unique pointer that stores the configuration of the heuristic that is used for pruning rules.

std::unique_ptr<ILiftFunctionConfig> liftFunctionConfigPtr_

An unique pointer that stores the configuration of the lift function that affects the quality of rules, depending on the number of labels for which they predict.