An Extension of the Method for Fuzzy Rules Extraction by Means of Artificial Neural Networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19520%2F13%3A%230002214" target="_blank" >RIV/47813059:19520/13:#0002214 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.3233/978-1-61499-264-6-65" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-264-6-65</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/978-1-61499-264-6-65" target="_blank" >10.3233/978-1-61499-264-6-65</a>
Alternative languages
Result language
angličtina
Original language name
An Extension of the Method for Fuzzy Rules Extraction by Means of Artificial Neural Networks
Original language description
Knowledge extraction from data in the form of rules is a widespread di- rection in data mining area, which allows to obtain interesting relationships in data from large databases in for a human easily understandable form. This paper deals withoneofthemethodsforextractionofrulesfromdatawhichextractrulesinform of a formula in considered fuzzy logic by means of artificial neural networks with special architecture. Using artificial neural networks in extraction process, above mentioned methods gain good approximation of analyzed data and thanks to spe- cial architecture allows to extract human-understandable knowledge. The method described in this paper was, however, missing any module, that is a standard part of themostofmethodsusedforrulesextractionfromdata,thatwouldallowtotheuser subjective selection of the best ratio between accuracy and comprehensibility of the model. This is especially important feature for solving data mining tasks called searching of concepts descriptio
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
—
Continuities
O - Projekt operacniho programu
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Frontiers in Artificial Intelligence and Applications 255
ISBN
978-1-61499-263-9
ISSN
—
e-ISSN
—
Number of pages
8
Pages from-to
65-73
Publisher name
IOS Press BV
Place of publication
Amsterdam
Event location
Amsterdam
Event date
Jun 26, 2013
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—