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

java.lang.Object
- elki.clustering.hierarchical.birch.EuclideanDistanceCriterion

All Implemented Interfaces:

BIRCHAbsorptionCriterion
```
public class EuclideanDistanceCriterion
extends java.lang.Object
implements BIRCHAbsorptionCriterion
```
Distance criterion. This is not found in the original work, but used in many implementation attempts: assign points if the Euclidean distances is below a threshold.

Since:

0.7.5

Author:

Erich Schubert

Field Summary

Fields
Modifier and Type Field Description

static EuclideanDistanceCriterion STATIC
Static instance.

Constructor Summary

Constructors
Constructor Description

EuclideanDistanceCriterion()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`squaredCriterion(ClusteringFeature f1, ClusteringFeature f2)`	Quality when merging two CFs.
`double`	`squaredCriterion(ClusteringFeature f1, NumberVector n)`	Quality of a CF when adding a data point

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

- Field Detail
  - STATIC
```
public static final EuclideanDistanceCriterion STATIC
```
    Static instance.
- Constructor Detail
  - EuclideanDistanceCriterion
```
public EuclideanDistanceCriterion()
```
- Method Detail
  - squaredCriterion
```
public double squaredCriterion(ClusteringFeature f1,
                               NumberVector n)
```
    Description copied from interface: BIRCHAbsorptionCriterion
    
    Quality of a CF when adding a data point
    
    Specified by:
    
    squaredCriterion in interface BIRCHAbsorptionCriterion
    
    Parameters:
    
    f1 - Clustering feature
    
    n - Data point
    
    Returns:
    
    Quality
  - squaredCriterion
```
public double squaredCriterion(ClusteringFeature f1,
                               ClusteringFeature f2)
```
    Description copied from interface: BIRCHAbsorptionCriterion
    
    Quality when merging two CFs.
    
    Specified by:
    
    squaredCriterion in interface BIRCHAbsorptionCriterion
    
    Parameters:
    
    f1 - First clustering feature
    
    f2 - Second clustering feature
    
    Returns:
    
    Quality