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

java.lang.Object
- elki.clustering.hierarchical.extraction.ClustersWithNoiseExtraction

All Implemented Interfaces:

elki.Algorithm, ClusteringAlgorithm<Clustering<Model>>
```
@Reference(authors="Erich Schubert, Michael Gertz",
           title="Semantic Word Clouds with Background Corpus Normalization and t-distributed Stochastic Neighbor Embedding",
           booktitle="ArXiV preprint, 1708.03569",
           url="http://arxiv.org/abs/1708.03569",
           bibkey="DBLP:journals/corr/abs-1708-03569")
@Priority(206)
public class ClustersWithNoiseExtraction
extends java.lang.Object
implements ClusteringAlgorithm<Clustering<Model>>
```
Extraction of a given number of clusters with a minimum size, and noise.
This will execute the highest-most cut where we retain k clusters, each with a minimum size, plus noise (single points that would only merge afterwards). If no such cut can be found, it returns a result with a relaxed k.
You need to specify: A) the minimum size of a cluster (it does not make much sense to use 1 - then it will simply execute all but the last k merges) and B) the desired number of clusters with at least minSize elements each.
Reference:
Erich Schubert, Michael Gertz
Semantic Word Clouds with Background Corpus Normalization and t-distributed Stochastic Neighbor Embedding
ArXiV preprint, 1708.03569
TODO: Also provide representatives and last merge height for clusters.

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes
Modifier and Type	Class	Description
`protected class`	`ClustersWithNoiseExtraction.Instance`	Instance for a single data set.
`static class`	`ClustersWithNoiseExtraction.Par`	Parameterization class.

Nested classes/interfaces inherited from interface elki.Algorithm
elki.Algorithm.Utils

Field Summary

Fields
Modifier and Type	Field	Description
`private HierarchicalClusteringAlgorithm`	`algorithm`	Clustering algorithm to run to obtain the hierarchy.
`private static elki.logging.Logging`	`LOG`	Class logger.
`private int`	`minClSize`	Minimum cluster size.
`private int`	`numCl`	Minimum number of clusters.

Constructor Summary

Constructors
Constructor	Description
`ClustersWithNoiseExtraction(HierarchicalClusteringAlgorithm algorithm, int numCl, int minClSize)`	Constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`Clustering<Model>`	`autorun(elki.database.Database database)`
`elki.data.type.TypeInformation[]`	`getInputTypeRestriction()`
`Clustering<Model>`	`run(ClusterMergeHistory merges)`	Process an existing result.

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

- Field Detail
  - LOG
```
private static final elki.logging.Logging LOG
```
    Class logger.
  - numCl
```
private int numCl
```
    Minimum number of clusters.
  - minClSize
```
private int minClSize
```
    Minimum cluster size.
  - algorithm
```
private HierarchicalClusteringAlgorithm algorithm
```
    Clustering algorithm to run to obtain the hierarchy.
- Constructor Detail
  - ClustersWithNoiseExtraction
```
public ClustersWithNoiseExtraction(HierarchicalClusteringAlgorithm algorithm,
                                   int numCl,
                                   int minClSize)
```
    Constructor.
    
    Parameters:
    
    algorithm - Algorithm to run
    
    numCl - Number of clusters
    
    minClSize - Minimum cluster size
- Method Detail
  - autorun
```
public Clustering<Model> autorun(elki.database.Database database)
```
    Specified by:
    
    autorun in interface elki.Algorithm
    
    Specified by:
    
    autorun in interface ClusteringAlgorithm<Clustering<Model>>
  - run
```
public Clustering<Model> run(ClusterMergeHistory merges)
```
    Process an existing result.
    
    Parameters:
    
    merges - Existing result in pointer representation.
    
    Returns:
    
    Clustering
  - getInputTypeRestriction
```
public elki.data.type.TypeInformation[] getInputTypeRestriction()
```
    Specified by:
    
    getInputTypeRestriction in interface elki.Algorithm