AutomaticStopClustering (S-Space Package 2.0.1 API)

java.lang.Object
- edu.ucla.sspace.clustering.AutomaticStopClustering

All Implemented Interfaces:

Clustering
```
public class AutomaticStopClustering
extends Object
implements Clustering
```
A Clustering implementation that iteratively computes the k-means clustering of a data set and fines the value of k that produced the most significant advantage compared to other values of k. This approach attempts to find a "knee" or "bend" in the graph of objective scores for k-means with different values of k. This clustering method is an implementation of the method specified in the following paper:
Pedersen, T and Kulkarni, A. (2006) Automatic Cluster Stopping with Criterion Functions and the Gap Statistic Sixth Annual Meeting of the North American Chapter of the Association for Computational Linguistics, 6, 276-279. Available here

Author:: Keith Stevens

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static class AutomaticStopClustering.Measure
The available stopping criteria.

Nested Classes
Modifier and Type	Class and Description
`static class`	`AutomaticStopClustering.Measure` The available stopping criteria.

Field Summary

Fields
Modifier and Type	Field and Description
`static String`	`CLUSTERING_METHOD` The number of clusters to stop clustering at.
`static String`	`NUM_CLUSTERS_END` The number of clusters to stop clustering at.
`static String`	`NUM_CLUSTERS_START` The number of clusters to start clustering at.
`static String`	`PK1_THRESHOLD` The number of clusters to stop clustering at.
`static String`	`PROPERTY_PREFIX` A property prefix used for properties.

Constructor Summary

Constructors
Constructor and Description

AutomaticStopClustering()

Constructors
Constructor and Description
`AutomaticStopClustering()`

Method Summary

Methods
Modifier and Type	Method and Description
`Assignments`	`cluster(Matrix m, int numClusters, Properties props)` Clusters the set of rows in the given `Matrix` into the specified number of clusters.
`Assignments`	`cluster(Matrix matrix, Properties props)` Clusters the set of rows in the given `Matrix` without a specified number of clusters (optional operation).

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

- Field Detail
  - PROPERTY_PREFIX
```
public static final String PROPERTY_PREFIX
```
    A property prefix used for properties.
    
    See Also:
    Constant Field Values
  - NUM_CLUSTERS_START
```
public static final String NUM_CLUSTERS_START
```
    The number of clusters to start clustering at.
    
    See Also:
    Constant Field Values
  - NUM_CLUSTERS_END
```
public static final String NUM_CLUSTERS_END
```
    The number of clusters to stop clustering at.
    
    See Also:
    Constant Field Values
  - CLUSTERING_METHOD
```
public static final String CLUSTERING_METHOD
```
    The number of clusters to stop clustering at.
    
    See Also:
    Constant Field Values
  - PK1_THRESHOLD
```
public static final String PK1_THRESHOLD
```
    The number of clusters to stop clustering at.
    
    See Also:
    Constant Field Values
- Constructor Detail
  - AutomaticStopClustering
```
public AutomaticStopClustering()
```
- Method Detail
  - cluster
```
public Assignments cluster(Matrix matrix,
                  Properties props)
```
    Clusters the set of rows in the given Matrix without a specified number of clusters (optional operation). The set of cluster assignments are returned for each row in the matrix.
    Iteratively computes the k-means clustering of the dataset m using a specified method for determineing when to automaticaly stop clustering.
    
    Specified by:
    
    cluster in interface Clustering
    
    Parameters:
    matrix - the Matrix whose row data points are to be clustered
    props - the properties to use for any parameters each clustering algorithm may need
    
    Returns:
    an array of Assignment instances that indicate zero or more clusters to which each row belongs.
  - cluster
```
public Assignments cluster(Matrix m,
                  int numClusters,
                  Properties props)
```
    Clusters the set of rows in the given Matrix into the specified number of clusters. The set of cluster assignments are returned for each row in the matrix.
    Iteratively computes the k-means clustering of the dataset m using a specified method for determineing when to automaticaly stop clustering.
    
    Specified by:
    
    cluster in interface Clustering
    
    Parameters:
    m - the Matrix whose row data points are to be clustered
    numClusters - the number of clusters to generate
    props - the properties to use for any parameters each clustering algorithm may need
    
    Returns:
    an array of Assignment instances that indicate zero or more clusters to which each row belongs.

Class AutomaticStopClustering

Nested Class Summary

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

PROPERTY_PREFIX

NUM_CLUSTERS_START

NUM_CLUSTERS_END

CLUSTERING_METHOD

PK1_THRESHOLD

Constructor Detail

AutomaticStopClustering

Method Detail

cluster

cluster