title: Grid topologies for the self-organizing map.
abstract: The original Self-Organizing Feature Map (SOFM) has been extended in many ways to suit different goals and application domains. However, the topologies of the map lattice that we can found in literature are nearly always square or, more rarely, hexagonal. In this paper we study alternative grid topologies, which are derived from the geometrical theory of tessellations. Experimental results are presented for unsupervised clustering, color image segmentation and classification tasks, which show that the differences among the topologies are statistically significant in most cases, and that the optimal topology depends on the problem at hand. A theoretical interpretation of these results is also developed.
authors.affiliation: Department of Computer Languages and Computer Science. University of Málaga, Bulevar Louis Pasteur, 35, 29071 Málaga, Spain. Electronic address: ezeqlr@lcc.uma.es.
authors.forename: Ezequiel
authors.initials: E
authors.lastname: López-Rubio
authors.affiliation: Department of Algebra, Geometry and Topology. University of Málaga, Bulevar Louis Pasteur, 33, 29071 Málaga, Spain. Electronic address: adiazramos@uma.es.
authors.forename: Antonio
authors.initials: A
authors.lastname: Díaz Ramos
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003116:Color; D016208:Databases, Factual; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016571:Neural Networks, Computer
keywords: Classification; Clustering; Image segmentation; Self-organizing map topologies; Tessellations