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Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning

Thomas Villmann

Villmann, Thomas

,

Andrea Bohnsack

Bohnsack, Andrea

e

17 dic 2016

Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning's Cover Image

Journal of Artificial Intelligence and Soft Computing Research

Volume 7 (2017): Numero 1 (Gennaio 2017)

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Pubblicato online: 17 dic 2016

Pagine: 65 - 81

DOI: https://doi.org/10.1515/jaiscr-2017-0005

Parole chiave
classification learning, vector quantization, prototype based learning

© 2016

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Villmann, Thomas

Germany

Bohnsack, Andrea

Germany

Germany

Kaden, Marika

Germany

Lingua:: Inglese

Frequenza di pubblicazione:: 4 volte all'anno
Argomenti della rivista:: Informatica, Intelligenza artificiale, Base dati e data mining

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