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 AddSingleScalePseudo "algorithm" that computes the global min/max for a relation across all attributes. AddSingleScale.ParParameterization class. AddUniformScalePseudo "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.KNNEvaluatorEvaluate kNN retrieval performance. EvaluateRetrievalPerformance.RetrievalPerformanceResultResult object for MAP scores. HopkinsStatisticClusteringTendencyThe Hopkins Statistic of Clustering Tendency measures the probability that a data set is generated by a uniform data distribution. HopkinsStatisticClusteringTendency.ParParameterization class. RankingQualityHistogram<O>Evaluate a distance function with respect to kNN queries.