An Algorithm for Multidimensional Data Clustering

S. J. Wan, S. K. M. Wong, and P. Prusinkiewicz

Abstract

A new divisive algorithm for multidimensional data clustering is suggested. Based on the minimization of the sum-of-squared-errors, the proposed method produces much smaller quantization errors than the median-cut and mean-split algorithms. It is also ohserved that the solutions obtained from our algorithm are close to the local optimal ones derived by the k-means iterative procedure.

Reference

S. J. Wan, S. K. M. Wong, and P. Prusinkiewicz. An algorithm for multidimensional data clustering. ACM Transactions on Mathematical Software. Volume 14 Issue 2, June 1988. Pages 153-162.

Download PDF here (1.2 Mb), or from the publisher's site.