BetulaLeafPreClustering (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

java.lang.Object
- elki.clustering.BetulaLeafPreClustering

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<MeanModel>>
```
@Priority(-100)
@Reference(authors="Andreas Lang and Erich Schubert",
           title="BETULA: Fast Clustering of Large Data with Improved BIRCH CF-Trees",
           booktitle="Information Systems",
           url="https://doi.org/10.1016/j.is.2021.101918",
           bibkey="DBLP:journals/is/LangS22")
public class BetulaLeafPreClustering
extends java.lang.Object
implements ClusteringAlgorithm<Clustering<MeanModel>>
```
BETULA-based clustering algorithm that simply treats the leafs of the CFTree as clusters. As this usually are smaller parts than actual clusters, we call this a preclustering, as it is primarily useful as a data simplification prior to, e.g., clustering. For actual clustering methods based on the leaves, please use BetulaGMM and BetulaLloydKMeans.
References:
Andreas Lang and Erich Schubert
BETULA: Fast Clustering of Large Data with Improved BIRCH CF-Trees
Information Systems

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class BetulaLeafPreClustering.Par
Parameterization class.
- Nested classes/interfaces inherited from interface elki.Algorithm
  Algorithm.Utils

Field Summary

Fields
Modifier and Type	Field	Description
`(package private) CFTree.Factory<?>`	`cffactory`	CFTree factory.
`private static Logging`	`LOG`	Class logger.
`(package private) boolean`	`storeIds`	Store ids

Constructor Summary

Constructors
Constructor Description

BetulaLeafPreClustering(CFTree.Factory<?> cffactory, boolean storeIds)
Constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`TypeInformation[]`	`getInputTypeRestriction()`	Get the input type restriction used for negotiating the data query.
`Clustering<MeanModel>`	`run(Relation<NumberVector> relation)`	Run the clustering algorithm.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface elki.clustering.ClusteringAlgorithm
autorun

- Field Detail
  - LOG
```
private static final Logging LOG
```
    Class logger.
  - cffactory
```
CFTree.Factory<?> cffactory
```
    CFTree factory.
  - storeIds
```
boolean storeIds
```
    Store ids
- Constructor Detail
  - BetulaLeafPreClustering
```
public BetulaLeafPreClustering(CFTree.Factory<?> cffactory,
                               boolean storeIds)
```
    Constructor.
    
    Parameters:
    
    cffactory - CFTree Factory
- Method Detail
  - getInputTypeRestriction
```
public TypeInformation[] getInputTypeRestriction()
```
    Description copied from interface: Algorithm
    
    Get the input type restriction used for negotiating the data query.
    
    Specified by:
    
    getInputTypeRestriction in interface Algorithm
    
    Returns:
    
    Type restriction
  - run
```
public Clustering<MeanModel> run(Relation<NumberVector> relation)
```
    Run the clustering algorithm.
    
    Parameters:
    
    relation - Input data
    
    Returns:
    
    Clustering