Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
482966 | European Journal of Operational Research | 2006 | 19 Pages |
Abstract
The minimum sum-of-squares clustering problem is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the former problem based on nonsmooth optimization techniques is developed. The issue of applying this algorithm to large data sets is discussed. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithm.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Adil M. Bagirov, John Yearwood,