Data sample reduction for classification of interval information using neural network sensitivity analysis / Piotr A. Kowalski, Piotr Kulczycki // W: Artificial intelligence : methodology, systems, and ... więcej

Data sample reduction for classification of interval information using neural network sensitivity analysis / Piotr A. Kowalski, Piotr Kulczycki // W: Artificial intelligence : methodology, systems, and applications : 14th international conference, AIMSA 2010, Varna, Bulgaria, September 8-10, 2010 : proceedings [Dokument elektroniczny] / eds. Darina Dicheva, Danail Dochev. – Berlin : Springer, 2010. – S. 271-272. – Tryb dostępu: https://home.agh.edu.pl/~kulpi/publ/Kowalski_Kulczycki_-_Artificial_Intelligence_Methodology_Systems_and_Applications_-_2010.pdf. – Bibliogr. 4 poz., Abstr. – ISBN 9783642154300. – ISBN 9783642154317

The aim of this paper is present a novel method of data sample reduction for classification of interval information. Its concept is based on the sensitivity analysis, inspired by artificial neural networks, ... więcej

The aim of this paper is present a novel method of data sample reduction for classification of interval information. Its concept is based on the sensitivity analysis, inspired by artificial neural networks, while the goal is to increase the number of proper classifications and primarily, calculation speed. The presented procedure was tested for the data samples representing classes obtained by random generator, real data from repository, with clustering also being used.