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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 Cover

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

Journal of Artificial Intelligence and Soft Computing Research
Volume 7 (2017): Issue 1 (January 2017)
By: Thomas Villmann,  Andrea Bohnsack and  Marika Kaden  
Open Access
|Dec 2016
Authors

Authors

Thomas Villmann

thomas.villmann@hs-mittweida.de

Germany

Andrea Bohnsack

Germany
Germany

Marika Kaden

Germany
DOI: https://doi.org/10.1515/jaiscr-2017-0005
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Language: English
Page range: 65 - 81
Published on: Dec 17, 2016
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
classification learning,
vector quantization,
prototype based learning
Related subjects:
Computer sciences,
Artificial intelligence,
Databases and data mining

© 2016 Thomas Villmann, Andrea Bohnsack, Marika Kaden, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 7 (2017): Issue 1 (January 2017)
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