Clustering (LIMES Core Library 1.7.5 API)

java.lang.Object
- org.aksw.limes.core.ml.algorithm.eagle.coala.Clustering

```
public class Clustering
extends Object
```
Author:

Klaus Lyko (lyko@informatik.uni-leipzig.de)

Constructor Summary

Constructors
Constructor Description

Clustering(ACache sourceCache, ACache targetCache, PropertyMapping propMap)

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`weka.core.Instances`	`computeSimilaritySpace(List<ALDecider.Triple> candidates)`	We first have to compute a similarity space for each candidate.
`static void`	`main(String[] args)`
`static void`	`wekaTest()`

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

- Constructor Detail
  - Clustering
```
public Clustering(ACache sourceCache,
                  ACache targetCache,
                  PropertyMapping propMap)
```
- Method Detail
  - computeSimilaritySpace
```
public weka.core.Instances computeSimilaritySpace(List<ALDecider.Triple> candidates)
```
    We first have to compute a similarity space for each candidate. That is, we compute a out of a list of most controversy candidate links (Triples, value close to 0.5). a vector of similarity values. E.g. for every String property.
    
    Parameters:
    
    candidates - Triples given by a committee, are source - target URIs and a double value giving information if its regarded as a match.
  - wekaTest
```
public static void wekaTest()
                     throws Exception
```
    Throws:
    
    Exception
  - main
```
public static void main(String[] args)
                 throws Exception
```
    Throws:
    
    Exception