Package de.lmu.ifi.dbs.elki.algorithm.statistics

Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)

See: Description

Class Summary

Class	Description
AddSingleScale	Pseudo "algorithm" that computes the global min/max for a relation across all attributes.
AddSingleScale.Parameterizer	Parameterization class.
AveragePrecisionAtK<O>	Evaluate a distance functions performance by computing the average precision at k, when ranking the objects by distance.
AveragePrecisionAtK.Parameterizer<O>	Parameterization class.
DistanceStatisticsWithClasses<O>	Algorithm to gather statistics over the distance distribution in the data set.
DistanceStatisticsWithClasses.Parameterizer<O>	Parameterization class.
EvaluateRankingQuality<V extends NumberVector>	Evaluate a distance function with respect to kNN queries.
EvaluateRankingQuality.Parameterizer<V extends NumberVector>	Parameterization class.
HopkinsStatisticClusteringTendency	The Hopkins Statistic of Clustering Tendency measures the probability that a data set is generated by a uniform data distribution.
HopkinsStatisticClusteringTendency.Parameterizer	Parameterization class.
MeanAveragePrecisionForDistance<O>	Evaluate a distance functions performance by computing the mean average precision, when ranking the objects by distance.
MeanAveragePrecisionForDistance.MAPResult	Result object for MAP scores.
MeanAveragePrecisionForDistance.Parameterizer<O>	Parameterization class.
RankingQualityHistogram<O>	Evaluate a distance function with respect to kNN queries.
RankingQualityHistogram.Parameterizer<O>	Parameterization class.

Package de.lmu.ifi.dbs.elki.algorithm.statistics Description

Statistical analysis algorithms

The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)