Reduction of Fuzzy Rule Bases Driven by the Coverage of Training Data

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F15%3AA1601DL3" target="_blank" >RIV/61988987:17610/15:A1601DL3 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Jazyk výsledku
angličtina
Název v původním jazyce
Reduction of Fuzzy Rule Bases Driven by the Coverage of Training Data
Popis výsledku v původním jazyce
We present a technique for size reduction of a base of fuzzy association rules which is created using an automated approach and which is intended for in- ference. Our approach is based on controlling the coverage of training data by the rule base and re-moving only such rules that do not increase that coverage. Experiments show that such reduction is very effective while affecting the outputs of infer- ence only very slightly.
Název v anglickém jazyce
Reduction of Fuzzy Rule Bases Driven by the Coverage of Training Data
Popis výsledku anglicky
We present a technique for size reduction of a base of fuzzy association rules which is created using an automated approach and which is intended for in- ference. Our approach is based on controlling the coverage of training data by the rule base and re-moving only such rules that do not increase that coverage. Experiments show that such reduction is very effective while affecting the outputs of infer- ence only very slightly.

Projekt
<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění
2015
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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