Year: 1988
Type: article
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 observed that the solutions obtained from our algorithm are close to the local optimal ones derived by the k-means iterative procedure.
DOI: 10.1145/45054.45056
Authors: S. J. Wan, S. K. M. Wong, P. Prusinkiewicz
Institution: University of Regina
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2052795606