Classification Model Based on Kohonen Maps

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F18%3A43898583" target="_blank" >RIV/60076658:12310/18:43898583 - isvavai.cz</a>

Výsledek na webu

<a href="http://ceur-ws.org/Vol-2300/Paper35.pdf" target="_blank" >http://ceur-ws.org/Vol-2300/Paper35.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Classification Model Based on Kohonen Maps

Popis výsledku v původním jazyce

The standard Kohonen map uses unsupervised learning and single Kohonen layer, which allows the usage for clustering and visualization. The number of model parameters is relatively small and their settings are therefore not so complicated. The aim of this paper is to introduce three modifications of this basic model so that it can be used for classification tasks. The first change is the transition to supervised learning by adding input data about the required outputs. The second modification is the implementation of the hierarchical model structure to improve the classification results. The third extension is the implementation of an optimization mechanism for setting the parameters of the model because the number of model parameters was extended and their adjustment was more difficult. The results of the experiments with modified model will be presented too.

Název v anglickém jazyce

Classification Model Based on Kohonen Maps

Popis výsledku anglicky

The standard Kohonen map uses unsupervised learning and single Kohonen layer, which allows the usage for clustering and visualization. The number of model parameters is relatively small and their settings are therefore not so complicated. The aim of this paper is to introduce three modifications of this basic model so that it can be used for classification tasks. The first change is the transition to supervised learning by adding input data about the required outputs. The second modification is the implementation of the hierarchical model structure to improve the classification results. The third extension is the implementation of an optimization mechanism for setting the parameters of the model because the number of model parameters was extended and their adjustment was more difficult. The results of the experiments with modified model will be presented too.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Conference Proceedings ADVANCED COMPUTER INFORMATION TECHNOLOGIES ACIT 2018

ISBN

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ISSN

1613-0073

e-ISSN

neuvedeno

Počet stran výsledku

4

Strana od-do

145-148

Název nakladatele

Ternopil National Economic University

Místo vydání

Ternopil, Ukraine

Místo konání akce

Ceske Budejovice, Czech Republic

Datum konání akce

1. 6. 2018

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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