Quality of Quantization and Visualization of Vectors Obtained by Neural Gas and Self-Organizing Map

Article type: Research Article

Authors: Kurasova, Olga^; | Molytė, Alma

Affiliations: Vilnius University, Institute of Mathematics and Informatics, Akademijos 4, LT-08663 Vilnius, Lithuania, E-mail: [email protected], [email protected] | Vilnius Pedagogical University, Studentų 39, LT-08106 Vilnius, Lithuania

Abstract: In this paper, the quality of quantization and visualization of vectors, obtained by vector quantization methods (self-organizing map and neural gas), is investigated. A multidimensional scaling is used for visualization of multidimensional vectors. The quality of quantization is measured by a quantization error. Two numerical measures for proximity preservation (Konig's topology preservation measure and Spearman's correlation coefficient) are applied to estimate the quality of visualization. Results of visualization (mapping images) are also presented.

Keywords: self-organizing map, neural gas, multidimensional scaling, quantization error, proximity preservation, Konig's measure, Spearman's rho

Journal: Informatica, vol. 22, no. 1, pp. 115-134, 2011