Data Mining by Symbolic Fuzzy Classifiers and Genetic Programming
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86083877" target="_blank" >RIV/61989100:27240/13:86083877 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
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 min- ing. 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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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
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
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
Advances in Intelligent Systems and Computing
ISBN
978-3-642-33226-5
ISSN
2194-5357
e-ISSN
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Number of pages
11
Pages from-to
273-283
Publisher name
Springer
Place of publication
Berlin
Event location
Ostrava
Event date
Sep 5, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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