| Package | Description | 
|---|---|
| de.lmu.ifi.dbs.elki.algorithm.statistics | 
 Statistical analysis algorithms. 
 | 
| Class and Description | 
|---|
| AddSingleScale
 Pseudo "algorithm" that computes the global min/max for a relation across all
 attributes. 
 | 
| AveragePrecisionAtK
 Evaluate a distance functions performance by computing the average precision
 at k, when ranking the objects by distance. 
 | 
| DistanceQuantileSampler
 Compute a quantile of a distance sample, useful for choosing parameters for
 algorithms. 
 | 
| DistanceStatisticsWithClasses
 Algorithm to gather statistics over the distance distribution in the data
 set. 
 | 
| EstimateIntrinsicDimensionality
 Estimate global average intrinsic dimensionality of a data set. 
 | 
| EvaluateRankingQuality
 Evaluate a distance function with respect to kNN queries. 
 | 
| EvaluateRetrievalPerformance
 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. 
 | 
| RangeQuerySelectivity
 Evaluate the range query selectivity. 
 | 
| RankingQualityHistogram
 Evaluate a distance function with respect to kNN queries. 
 | 
Copyright © 2019 ELKI Development Team. License information.