Multilayer feedforward neural networks based on multi-valued neurons – Bc. Miroslav Hlaváček
Bc. Miroslav Hlaváček
Master's thesis
Multilayer feedforward neural networks based on multi-valued neurons
Multilayer feedforward neural networks based on multi-valued neurons
Abstract:
Vícevrstvá dopředná neuronová síť s vícehodnotovými neurony (MLMVN) je model použitelný pro strojové učení schopný klasifikace (do více tříd) a aproximace funkcí. Výsledky dosahované s MLMVN jsou srovnatelné s nejlepšími známými nástroji strojového učení, jako například "support vector machines." Tato práce srovnává klasickou vícevrstvou neuronovou síť (často označována jako "multilayer perceptron …moreAbstract:
Multilayer feedforward neural network with multi-valued neurons (MLMVN) is machine learning tool capable of multi-class classification and function approximation. MLMVN’s performance is comparable with, and in some cases outperforms, best machine learning tools utilized today like support vector machines. This work compares classical multilayer feedforward networks (often referred to as multilayer …more
Language used: English
Date on which the thesis was submitted / produced: 26. 5. 2014
Identifier:
https://is.muni.cz/th/bf067/
Thesis defence
- Date of defence: 24. 6. 2014
- Supervisor: Mgr. Marek Grác, Ph.D.
- Reader: Igor Aizenberg, Ph.D.
Citation record
Full text of thesis
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Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsMaster programme / field:
Informatics / Artificial Intelligence and Natural Language Processing
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