@inproceedings{b63932d0d65c4f86a96de4a3a19584fd,
title = "Prototype-based threshold rules",
abstract = "Understanding data is usually done extracting fuzzy or crisp logical rules using neurofuzzy systems, decision trees and other approaches. Prototypebased rules are an interesting alternative providing in many cases simpler, more accurate and more comprehensible description of the data. Algorithm for generation of threshold prototype-based rules are described and a comparison with neurofuzzy systems on a number of datasets provided. Results show that systems for data understanding generating prototypes deserve at least the same attention as that enjoyed by the neurofuzzy systems.",
author = "Marcin Blachnik and Wlodzislaw Duch",
year = "2006",
doi = "10.1007/11893295\_113",
language = "English",
isbn = "3540464840",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1028--1037",
booktitle = "Neural Information Processing - 13th International Conference, ICONIP 2006, Proceedings",
address = "Germany",
note = "13th International Conference on Neural Information Processing, ICONIP 2006 ; Conference date: 03-10-2006 Through 06-10-2006",
}