An Extension of the Method for Fuzzy Rules Extraction by Means of Artificial Neural Networks
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
An Extension of the Method for Fuzzy Rules Extraction by Means of Artificial Neural Networks
Popis výsledku v původním jazyce
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
Název v anglickém jazyce
An Extension of the Method for Fuzzy Rules Extraction by Means of Artificial Neural Networks
Popis výsledku anglicky
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
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
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Návaznosti výsledku
Projekt
—
Návaznosti
O - Projekt operacniho programu
Ostatní
Rok uplatnění
2013
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Frontiers in Artificial Intelligence and Applications 255
ISBN
978-1-61499-263-9
ISSN
—
e-ISSN
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Počet stran výsledku
8
Strana od-do
65-73
Název nakladatele
IOS Press BV
Místo vydání
Amsterdam
Místo konání akce
Amsterdam
Datum konání akce
26. 6. 2013
Typ akce podle státní příslušnosti
EUR - Evropská akce
Kód UT WoS článku
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