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 classDistanceStatisticsWithClasses<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.