File statistics_subset.hpp

class IStatisticsSubset

#include <statistics_subset.hpp>

Defines an interface for all classes that provide access to a subset of the statistics that are stored by an instance of the class IStatistics and allows to calculate the scores to be predicted by rules that cover such a subset.

Subclassed by IWeightedStatisticsSubset

Public Functions

inline virtual ~IStatisticsSubset()

virtual bool hasNonZeroWeight(uint32 statisticIndex) const = 0

Returns whether the statistics at a specific index have a non-zero weight or not.

Returns:

True, if the statistics at the given index have a non-zero weight, false otherwise

virtual void addToSubset(uint32 statisticIndex) = 0

Adds the statistics at a specific index to the subset in order to mark it as covered by the condition that is currently considered for refining a rule.

This function must be called repeatedly for each statistic that is covered by the current condition, immediately after the invocation of the function IImmutableWeightedStatistics::createSubset. If a rule has already been refined, each of these statistics must have been marked as covered earlier via the function IWeightedStatistics::addCoveredStatistic and must not have been marked as uncovered via the function IWeightedStatistics::removeCoveredStatistic.

This function is supposed to update any internal state of the subset that relates to the statistics that are covered by the current condition, i.e., to compute and store local information that is required by the other functions that will be called later. Any information computed by this function is expected to be reset when invoking the function resetSubset for the next time.

Parameters:

statisticIndex – The index of the covered statistic

virtual const IScoreVector &calculateScores() = 0

Calculates and returns the scores to be predicted by a rule that covers all statistics that have been added to the subset via the function addToSubset, as well as a numerical score that assesses the overall quality of the predicted scores.

Returns:

A reference to an object of type IScoreVector that stores the scores to be predicted by the rule for each considered label, as well as a numerical score that assesses their overall quality