Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
481800 | European Journal of Operational Research | 2007 | 19 Pages |
Abstract
One of the most promising approaches for clustering is based on methods of mathematical programming. In this paper we propose new optimization methods based on DC (Difference of Convex functions) programming for hierarchical clustering. A bilevel hierarchical clustering model is considered with different optimization formulations. They are all nonconvex, nonsmooth optimization problems for which we investigate attractive DC optimization Algorithms called DCA. Numerical results on some artificial and real-world databases are reported. The results demonstrate that the proposed algorithms are more efficient than related existing methods.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Le Thi Hoai An, Le Hoai Minh, Pham Dinh Tao,