| Package | Description | 
|---|---|
| de.lmu.ifi.dbs.elki.algorithm.outlier.clustering | Clustering based outlier detection. | 
| de.lmu.ifi.dbs.elki.evaluation.clustering.internal | Internal evaluation measures for clusterings. | 
| Class and Description | 
|---|
| NoiseHandling Options for handling noise in internal measures. | 
| Class and Description | 
|---|
| EvaluateCIndex Compute the C-index of a data set. | 
| EvaluateConcordantPairs Compute the Gamma Criterion of a data set. | 
| EvaluateDaviesBouldin Compute the Davies-Bouldin index of a data set. | 
| EvaluatePBMIndex Compute the PBM of a data set
 Reference:
 
 M. | 
| EvaluateSilhouette Compute the silhouette of a data set. | 
| EvaluateSimplifiedSilhouette Compute the simplified silhouette of a data set. | 
| EvaluateSquaredErrors Evaluate a clustering by reporting the squared errors (SSE, SSQ), as used by
 k-means. | 
| EvaluateVarianceRatioCriteria Compute the Variance Ratio Criteria of a data set. | 
| NoiseHandling Options for handling noise in internal measures. | 
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.