Data mining by symbolic fuzzy classifiers and genetic programming

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86088872" target="_blank" >RIV/61989100:27240/13:86088872 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/13:86088872
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-33227-2_28" target="_blank" >http://dx.doi.org/10.1007/978-3-642-33227-2_28</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-33227-2_28" target="_blank" >10.1007/978-3-642-33227-2_28</a>

Result language
angličtina
Original language name
Data mining by symbolic fuzzy classifiers and genetic programming
Original language description
There are various techniques for data mining and data analysis. Among them, hybrid approaches combining two or more algorithms gain importance as the complexity and dimension of real world data sets grows. In this paper, we present an application of evolutionary-fuzzy classification technique for data mining. Genetic programming is deployed to evolve a fuzzy classifier and an example of real world application is presented.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Intelligent Systems and Computing. Volume 210
ISBN
978-3-319-00541-6
ISSN
2194-5357
e-ISSN
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Number of pages
10
Pages from-to
273-282
Publisher name
Springer
Place of publication
Berlin
Event location
Ostrava
Event date
Jun 3, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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