Experiments to compare rough sets and vector quantization with the self-organizing algorithm
Raisa R. Szabo · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
This paper presents a comparison study of the rough set approach and Kohonen's vector quantization with the self- organizing algorithm. The main idea behind this research is the fact that neither the rough set nor Kohonen's neural network approaches require a prior knowledge of data distribution. The paradigms are compared in terms of their methods for the calculation of an accuracy of approximation and classification, reduction of non-significant attributes, minimal subset of attributes, and the uncertainty associated with the decision making process.