NaiveAgglomerativeHierarchicalClustering4 (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

java.lang.Object
- tutorial.clustering.NaiveAgglomerativeHierarchicalClustering4<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, HierarchicalClusteringAlgorithm
```
@Reference(authors="R. M. Cormack",
           title="A Review of Classification",
           booktitle="Journal of the Royal Statistical Society. Series A, Vol. 134, No. 3",
           url="https://doi.org/10.2307/2344237",
           bibkey="doi:10.2307/2344237")
public class NaiveAgglomerativeHierarchicalClustering4<O>
extends java.lang.Object
implements HierarchicalClusteringAlgorithm
```
This tutorial will step you through implementing a well known clustering algorithm, agglomerative hierarchical clustering, in multiple steps.
This is the third step, where we add support for different linkage strategies.
This is the naive O(n³) algorithm. See SLINK for a much faster algorithm (however, only for single-linkage).
Reference (for the update formulas):
R. M. Cormack
A Review of Classification
Journal of the Royal Statistical Society. Series A, Vol. 134, No. 3

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class NaiveAgglomerativeHierarchicalClustering4.Linkage
Different linkage strategies.
- Nested classes/interfaces inherited from interface elki.Algorithm
  Algorithm.Utils

Field Summary

Fields
Modifier and Type	Field	Description
`(package private) Distance<? super O>`	`distance`	Distance function used.
`(package private) NaiveAgglomerativeHierarchicalClustering4.Linkage`	`linkage`	Current linkage in use.
`private static Logging`	`LOG`	Class logger

Constructor Summary

Constructors
Constructor	Description
`NaiveAgglomerativeHierarchicalClustering4(Distance<? super O> distance, NaiveAgglomerativeHierarchicalClustering4.Linkage linkage)`	Constructor.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`TypeInformation[]`	`getInputTypeRestriction()`	Get the input type restriction used for negotiating the data query.
`ClusterMergeHistory`	`run(Relation<O> relation)`	Run the algorithm
`protected static int`	`triangleSize(int x)`	Compute the size of a complete x by x triangle (minus diagonal)

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

Methods inherited from interface elki.clustering.hierarchical.HierarchicalClusteringAlgorithm
autorun

- Field Detail
  - LOG
```
private static final Logging LOG
```
    Class logger
  - distance
```
Distance<? super O> distance
```
    Distance function used.
  - linkage
```
NaiveAgglomerativeHierarchicalClustering4.Linkage linkage
```
    Current linkage in use.
- Constructor Detail
  - NaiveAgglomerativeHierarchicalClustering4
```
public NaiveAgglomerativeHierarchicalClustering4(Distance<? super O> distance,
                                                 NaiveAgglomerativeHierarchicalClustering4.Linkage linkage)
```
    Constructor.
    
    Parameters:
    
    distance - Distance function to use
    
    linkage - Linkage strategy
- 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 ClusterMergeHistory run(Relation<O> relation)
```
    Run the algorithm
    
    Parameters:
    
    relation - Relation
    
    Returns:
    
    Clustering hierarchy
  - triangleSize
```
protected static int triangleSize(int x)
```
    Compute the size of a complete x by x triangle (minus diagonal)
    
    Parameters:
    
    x - Offset
    
    Returns:
    
    Size of complete triangle