Classification of economic data into multiple classes by means of evolutionary methods

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F13%3A00214248" target="_blank" >RIV/62156489:43110/13:00214248 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.11118/actaun201361072445" target="_blank" >http://dx.doi.org/10.11118/actaun201361072445</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.11118/actaun201361072445" target="_blank" >10.11118/actaun201361072445</a>

Result language
angličtina
Original language name
Classification of economic data into multiple classes by means of evolutionary methods
Original language description
In this contribution we deal with an automatic classification of economic data into multiple classes. A classifier created by grammatical evolution is used to determine the data sample membership into one of the defined classes. The grammar rules used for classifier structure creation are presented. The performance of our classifier is compared with multilayer perceptron neural network classifier and Kohonen neural network classifier. We used a survey data of consumer behaviour in food market in Czech Republic.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
ISSN
1211-8516
e-ISSN
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Volume of the periodical
61
Issue of the periodical within the volume
7
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
5
Pages from-to
2445-2449
UT code for WoS article
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EID of the result in the Scopus database
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