Clustering Stream Data by Regression Analysis

Motoyoshi, M., Miura, T. and Shioya, I.

In data clustering, many approaches have been proposed such as K-means method and hierarchical method. One of the problems is that the results depend heavily on initial values and criterion to combine clusters. In this investigation, we propose a new method to cluster stream data while avoiding this deficiency. Here we assume there exists aspects of local regression in data. Then we develop our theory to combine clusters using F values by regression analysis as criterion and to adapt to stream data. We examine experiments and show how well the theory works.

Cite as: Motoyoshi, M., Miura, T. and Shioya, I. (2004). Clustering Stream Data by Regression Analysis. In Proc. Australasian Workshop on Data Mining and Web Intelligence (DMWI2004), Dunedin, New Zealand. CRPIT, 32. Purvis, M., Ed. ACS. 115-120.

(from crpit.com) (local if available)