File feature_vector_equal.hpp

class EqualFeatureVector : public IFeatureVector
#include <feature_vector_equal.hpp>

A feature vector that does not actually store any values. It is used in cases where all training examples have the same value for a certain feature.

Public Functions

virtual void searchForRefinement(FeatureBasedSearch &featureBasedSearch, IWeightedStatisticsSubset &statisticsSubset, SingleRefinementComparator &comparator, uint32 numExamlesWithNonZeroWeights, uint32 minCoverage, Refinement &refinement) const override

Conducts a search for the best refinement of an existing rule that can be created from a this feature vector.

Parameters:

  • featureBasedSearch – A reference to an object of type FeatureBasedSearch that should be used for conducting the search

  • statisticsSubset – A reference to an object of type IWeightedStatisticsSubset that provides access to weighted statistics about the labels of the training examples, which should serve as the basis for evaluating the quality of potential refinements

  • comparator – A reference to an object of type SingleRefinementComparator that should be used for comparing potential refinements

  • numExamplesWithNonZeroWeights – The total number of examples with non-zero weights that may be covered by a refinement

  • minCoverage – The minimum number of examples that must be covered by the refinement

  • refinement – A reference to an object of type Refinement that should be used for storing the properties of the best refinement that is found

virtual void searchForRefinement(FeatureBasedSearch &featureBasedSearch, IWeightedStatisticsSubset &statisticsSubset, FixedRefinementComparator &comparator, uint32 numExamlesWithNonZeroWeights, uint32 minCoverage, Refinement &refinement) const override

Conducts a search for the best refinement of an existing rule that can be created from a this feature vector.

Parameters:

  • featureBasedSearch – A reference to an object of type FeatureBasedSearch that should be used for conducting the search

  • statisticsSubset – A reference to an object of type IWeightedStatisticsSubset that provides access to weighted statistics about the labels of the training examples, which should serve as the basis for evaluating the quality of potential refinements

  • comparator – A reference to an object of type MultiRefinementComparator that should be used for comparing potential refinements

  • numExamplesWithNonZeroWeights – The total number of examples with non-zero weights that may be covered by a refinement

  • minCoverage – The minimum number of examples that must be covered by the refinement

  • refinement – A reference to an object of type Refinement that should be used for storing the properties of the best refinement that is found

virtual void updateCoverageMaskAndStatistics(const Interval &interval, CoverageMask &coverageMask, uint32 indicatorValue, IWeightedStatistics &statistics) const override

Updates a given CoverageMask and IWeightedStatistics depending on the indices of training examples included in a specific Interval.

Parameters:

  • interval – A reference to an object of type Interval that includes the indices of all covered training examples

  • coverageMask – A reference to an object of type CoverageMask that should be updated

  • indicatorValue – The indicator value that should be used for updating the given CoverageMask

  • statistics – A reference to an object of type IWeightedStatistics that should be updated

virtual std::unique_ptr<IFeatureVector> createFilteredFeatureVector(std::unique_ptr<IFeatureVector> &existing, const Interval &interval) const override

Creates and returns a copy of this vector that does only store the feature values of training examples included in a given Interval.

Parameters:

  • existing – A reference to an unique pointer that stores an object of type IFeatureVector that may be reused or a null pointer, if no such object is available

  • interval – A reference to an object of type Interval that includes the indices of the training examples to be retained

Returns:

An unique pointer to an object of type IFeatureVector that has been created

virtual std::unique_ptr<IFeatureVector> createFilteredFeatureVector(std::unique_ptr<IFeatureVector> &existing, const CoverageMask &coverageMask) const override

Creates and returns a copy of this vector that does only store the feature values of training examples marked as covered according to a given CoverageMask.

Parameters:

  • existing – A reference to an unique pointer that stores an object of type IFeatureVector that may be reused or a null pointer, if no such object is available

  • coverageMask – A reference to an object of type CoverageMask that specifies the indices of the training examples to be retained

Returns:

An unique pointer to an object of type IFeatureVector that has been created