Model Selection and Stability in Spectral Clustering
Zeev Volkovich, Renata Avros
2012
Abstract
An open problem in spectral clustering concerning of finding automatically the number of clusters is studied. We generalize the method for the scale parameter selecting offered in the Ng-Jordan-Weiss (NJW) algorithm and reveal a connection with the distance learning methodology. Values of the scaling parameter estimated via clustering of samples drawn are considered as a cluster stability attitude such that the clusters quantity corresponding to the most concentrated distribution is accepted as “true” number of clusters. Numerical experiments provided demonstrate high potential ability of the offered method.
DownloadPaper Citation
in Harvard Style
Volkovich Z. and Avros R. (2012). Model Selection and Stability in Spectral Clustering . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012) ISBN 978-989-8565-29-7, pages 25-34. DOI: 10.5220/0004132700250034
in Bibtex Style
@conference{kdir12,
author={Zeev Volkovich and Renata Avros},
title={Model Selection and Stability in Spectral Clustering },
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012)},
year={2012},
pages={25-34},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004132700250034},
isbn={978-989-8565-29-7},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2012)
TI - Model Selection and Stability in Spectral Clustering
SN - 978-989-8565-29-7
AU - Volkovich Z.
AU - Avros R.
PY - 2012
SP - 25
EP - 34
DO - 10.5220/0004132700250034