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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

  • DOI - Digital Object Identifier

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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

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

  • e-ISSN

  • 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