Package elki.algorithm.statistics

Statistical analysis algorithms.

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

Class Summary

Class	Description
AddSingleScale	Pseudo "algorithm" that computes the global min/max for a relation across all attributes.
AddSingleScale.Par	Parameterization class.
AddUniformScale	Pseudo "algorithm" that computes the global min/max for a relation across all attributes.
AveragePrecisionAtK<O>	Evaluate a distance functions performance by computing the average precision at k, when ranking the objects by distance.
DistanceQuantileSampler<O>	Compute a quantile of a distance sample, useful for choosing parameters for algorithms.
DistanceQuantileSampler.Par<O>	Parameterization class
DistanceStatisticsWithClasses<O>	Algorithm to gather statistics over the distance distribution in the data set.
EvaluateRankingQuality<V extends NumberVector>	Evaluate a distance function with respect to kNN queries.
EvaluateRetrievalPerformance<O>	Evaluate a distance functions performance by computing the mean average precision, ROC, and NN classification performance when ranking the objects by distance.
EvaluateRetrievalPerformance.KNNEvaluator	Evaluate kNN retrieval performance.
EvaluateRetrievalPerformance.RetrievalPerformanceResult	Result object for MAP scores.
HopkinsStatisticClusteringTendency	The Hopkins Statistic of Clustering Tendency measures the probability that a data set is generated by a uniform data distribution.
HopkinsStatisticClusteringTendency.Par	Parameterization class.
RankingQualityHistogram<O>	Evaluate a distance function with respect to kNN queries.