On the Improvement of Support Vector Techniques for Clustering by Means of Whitening Transform

In this letter, we suggest a novel method for clustering, based on finding the smallest enclosing hyperellipse in arbitrary Hilbert spaces. In particular, we show that the one class support vector method that finds the minimum bounding hypersphere, under the whitening transform, becomes a method for finding the minimum bounding hyperellipse. Afterwards, we generalize the method in order to find the minimum bounding hyperellipse in arbitrary Hilbert spaces. We illustrate the power of the proposed methods in clustering applications.