Artem Barger created MATH-1330:
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Summary: KMeans clustering algorithm, doesn't support clustering
of sparse input data.
Key: MATH-1330
URL: https://issues.apache.org/jira/browse/MATH-1330
Project: Commons Math
Issue Type: Improvement
Reporter: Artem Barger
Currently `KMeansPlusPlusClusterer` class require from generic parameter `T` to
extend from `Clusterable` interface, which is:
```
public interface Clusterable {
/**
* Gets the n-dimensional point.
*
* @return the point array
*/
double[] getPoint();
}
```
i.e. returns dense representation of the clusterable data, hence making it
impossible to efficiently compute kmeans clustering on big dimensional, but
very sparse data. I think it will be much better if `Clusterable` interface
will return a `Vector` allowing usage of `SparceVector`s while clustering the
data. Of course `KMeansPlusPlusClusterer` implementation and I assume other
clustering implementations should be refactored accordingly to support this.
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