See: Description

| Class | Description | 
|---|---|
| AddSingleScale | 
 Pseudo "algorithm" that computes the global min/max for a relation across all
 attributes. 
 | 
| AddSingleScale.Parameterizer | 
 Parameterization class. 
 | 
| AveragePrecisionAtK<V,D extends NumberDistance<D,?>> | 
 Evaluate a distance functions performance by computing the average precision
 at k, when ranking the objects by distance. 
 | 
| AveragePrecisionAtK.Parameterizer<V extends NumberVector<?>,D extends NumberDistance<D,?>> | 
 Parameterization class. 
 | 
| DistanceStatisticsWithClasses<O,D extends NumberDistance<D,?>> | 
 Algorithm to gather statistics over the distance distribution in the data
 set. 
 | 
| DistanceStatisticsWithClasses.Parameterizer<O,D extends NumberDistance<D,?>> | 
 Parameterization class. 
 | 
| EvaluateRankingQuality<V extends NumberVector<?>,D extends NumberDistance<D,?>> | 
 Evaluate a distance function with respect to kNN queries. 
 | 
| EvaluateRankingQuality.Parameterizer<V extends NumberVector<?>,D extends NumberDistance<D,?>> | 
 Parameterization class. 
 | 
| RankingQualityHistogram<O,D extends NumberDistance<D,?>> | 
 Evaluate a distance function with respect to kNN queries. 
 | 
| RankingQualityHistogram.Parameterizer<O,D extends NumberDistance<D,?>> | 
 Parameterization class. 
 | 
Statistical analysis algorithms
The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)