Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical |
Hierarchical agglomerative clustering (HAC).
|
tutorial.clustering |
Classes from the tutorial on implementing a custom k-means variation.
|
Modifier and Type | Class and Description |
---|---|
class |
PointerDensityHierarchyRepresentationResult
Extended pointer representation useful for HDBSCAN.
|
Modifier and Type | Method and Description |
---|---|
PointerHierarchyRepresentationResult |
HierarchicalClusteringAlgorithm.run(Database db) |
PointerHierarchyRepresentationResult |
SLINK.run(Database database,
Relation<O> relation)
Performs the SLINK algorithm on the given database.
|
PointerHierarchyRepresentationResult |
AnderbergHierarchicalClustering.run(Database db,
Relation<O> relation)
Run the algorithm
|
PointerHierarchyRepresentationResult |
AGNES.run(Database db,
Relation<O> relation)
Run the algorithm
|
Modifier and Type | Method and Description |
---|---|
PointerHierarchyRepresentationResult |
NaiveAgglomerativeHierarchicalClustering4.run(Database db,
Relation<O> relation)
Run the algorithm
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.