| 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.