NaiveAgglomerativeHierarchicalClustering1 (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

java.lang.Object
- tutorial.clustering.NaiveAgglomerativeHierarchicalClustering1<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm
```
public class NaiveAgglomerativeHierarchicalClustering1<O>
extends java.lang.Object
implements Algorithm
```
This tutorial will step you through implementing a well known clustering algorithm, agglomerative hierarchical clustering, in multiple steps.
This is the first step, where we implement it with single linkage only, and extract a fixed number of clusters. The follow up variants will be made more flexible.
This is the naive O(n³) algorithm. See SLINK for a much faster algorithm (however, only for single-linkage).

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary
- 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.
`private static Logging`	`LOG`	Class logger
`(package private) int`	`numclusters`	Threshold, how many clusters to extract.

Constructor Summary

Constructors
Constructor Description

NaiveAgglomerativeHierarchicalClustering1(Distance<? super O> distance, int numclusters)
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<Model>`	`run(Relation<O> relation)`	Perform HAC

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

Methods inherited from interface elki.Algorithm
autorun

- Field Detail
  - LOG
```
private static final Logging LOG
```
    Class logger
  - distance
```
Distance<? super O> distance
```
    Distance function used.
  - numclusters
```
int numclusters
```
    Threshold, how many clusters to extract.
- Constructor Detail
  - NaiveAgglomerativeHierarchicalClustering1
```
public NaiveAgglomerativeHierarchicalClustering1(Distance<? super O> distance,
                                                 int numclusters)
```
    Constructor.
    
    Parameters:
    
    distance - Distance function to use
    
    numclusters - Number of clusters
- 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<Model> run(Relation<O> relation)
```
    Perform HAC
    
    Parameters:
    
    relation - Data relation
    
    Returns:
    
    Clustering