Piecewise-Linear Neural Networks and Their Relationship to Rule Extraction from Data

Number of the records: 1

1.

SYSNO ASEP	0041967
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Piecewise-Linear Neural Networks and Their Relationship to Rule Extraction from Data
Title	Po částech lineární neuronové sítě a jejich vztah k získávání pravidel z dat
Author(s)	Holeňa, Martin (UIVT-O)_{SAI, RID}
Source Title	Neural Computation - ISSN 0899-7667 Roč. 18, č. 11 (2006), s. 2813-2853
Number of pages	41 s.
Language	eng - English
Country	US - United States
Keywords	extraction of rules from data ; artificial neural networks
Subject RIV	IN - Informatics, Computer Science
R&D Projects	GA201/05/0325 GA ČR - Czech Science Foundation (CSF)
	GA201/05/0557 GA ČR - Czech Science Foundation (CSF)
	IAA100300503 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR)
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
UT WOS	000240735600010
EID SCOPUS	33750596411
DOI	10.1162/neco.2006.18.11.2813
Annotation	The paper addresses the topic of extracting logical rules from data by means of artificial neural networks. The approach based on piecewise-linear neural networks is revisited, which has already been used for the extraction of Boolean rules in the past, and it is shown that this approach can be important also for the extraction of fuzzy rules.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2007

Number of the records: 1