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.)