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

java.lang.Object
- tutorial.clustering.CFSFDP<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<SimplePrototypeModel<DBID>>>
```
public class CFSFDP<O>
extends java.lang.Object
implements ClusteringAlgorithm<Clustering<SimplePrototypeModel<DBID>>>
```
Tutorial code for Clustering by fast search and find of density peaks.
While the authors named this "fast", the runtime clearly is O(n²) making this a rather slow method compared to k-means. The Science paper also does not do a good comparison to existing methods such as HDBSCAN, OPTICS, and mean-shift clustering.
This is an adaptation of the original method to use priority search for accelerations, so the runtime can be better than pairwise distance computations (but supposedly still is O(n²))
Reference:
A. Rodriguez and A. Laio
Clustering by fast search and find of density peaks
Science 344 (6191), 2014

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class CFSFDP.Par<O>
Class parameterizer.
- Nested classes/interfaces inherited from interface elki.Algorithm
  Algorithm.Utils

Field Summary

Fields
Modifier and Type	Field	Description
`protected double`	`dc`	Distance cutoff.
`protected Distance<? super O>`	`distance`	Distance function used.
`protected int`	`k`	Number of clusters to find.

Constructor Summary

Constructors
Modifier Constructor Description

protected CFSFDP(Distance<? super O> distance, double dc, int k)
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<SimplePrototypeModel<DBID>>`	`run(Relation<O> relation)`	Perform CFSFDP clustering.

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
  - distance
```
protected Distance<? super O> distance
```
    Distance function used.
  - dc
```
protected double dc
```
    Distance cutoff.
  - k
```
protected int k
```
    Number of clusters to find.
- Constructor Detail
  - CFSFDP
```
protected CFSFDP(Distance<? super O> distance,
                 double dc,
                 int k)
```
    Constructor.
    
    Parameters:
    
    distance - distance function
    
    dc - distance cutoff
    
    k - number of clusters
- Method Detail
  - run
```
public Clustering<SimplePrototypeModel<DBID>> run(Relation<O> relation)
```
    Perform CFSFDP clustering.
    
    Parameters:
    
    relation - data relation
    
    Returns:
    
    clustering
  - 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