Comparison of Different Non-statistical Classification Methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F12%3A00190768" target="_blank" >RIV/62156489:43110/12:00190768 - 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
Comparison of Different Non-statistical Classification Methods
Original language description
In this article, we aim to compare different methods usable for solving classification problems. A substantial number of methods that are not based on mathematical statistics may be used. Exploring these methods is interesting, because they are often capable of solving problems, which are not easily solvable using classificators based purely on mathematical statistics. There are many approaches available such as support vector machines, neural networks, evolutionary algorithms, parallel coordinates, etc. In this article, we concentrate on describing different neural network approaches, parallel coordinates and genetic algorithms. Neural networks come in many flavors (e.g. multi-layer perceptron, non-linear autoregressive networks) and they have achieved some recognition. Genetic algorithms also have been used for classification many times before, but with mixed results. In this article, we describe and evaluate different capabilities of these methods when used for economic data. This f
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP403%2F11%2F2085" target="_blank" >GAP403/11/2085: Construction of Methods for Multifactor Assessment of Company complex Performance in Selected Sectors.</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 30th International Conference Mathematical Methods in Economics 2012
ISBN
978-80-7248-779-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
727-732
Publisher name
Silesian University in Opava, School of Business Administration in Karviná
Place of publication
Karviná
Event location
Karviná
Event date
Jan 1, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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