Supervised Competition Using Joined Growing Neural Gas

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F14%3A86090545" target="_blank" >RIV/61989100:27740/14:86090545 - isvavai.cz</a>

Výsledek na webu

<a href="http://sdiwc.net/digital-library/supervised-competition-using-joined-growing-neural-gas" target="_blank" >http://sdiwc.net/digital-library/supervised-competition-using-joined-growing-neural-gas</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Supervised Competition Using Joined Growing Neural Gas

Popis výsledku v původním jazyce

Competitive learning is well-known method to process data. Various goals may be achieved using competi- tive learning such as classifcation or vector quantiza- tion. In this paper, we present a different insight into the principle of supervised competitive learning. An in- novative approach to the supervised self-organization is suggested. The method is based on different handling of input data labels which encode the classifcation. When the label has appropriate format then it is possible to use it within the competitive process in the same way as any input data element. Such approach is as effective as standard supervised methods and has some positive attributes such as the soft classification ability.

Název v anglickém jazyce

Supervised Competition Using Joined Growing Neural Gas

Popis výsledku anglicky

Competitive learning is well-known method to process data. Various goals may be achieved using competi- tive learning such as classifcation or vector quantiza- tion. In this paper, we present a different insight into the principle of supervised competitive learning. An in- novative approach to the supervised self-organization is suggested. The method is based on different handling of input data labels which encode the classifcation. When the label has appropriate format then it is possible to use it within the competitive process in the same way as any input data element. Such approach is as effective as standard supervised methods and has some positive attributes such as the soft classification ability.

Druh

O - Ostatní výsledky

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/EE2.3.30.0055" target="_blank" >EE2.3.30.0055: Nové kreativní týmy v prioritách vědeckého bádání</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

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