Variants and Performances of Novel Direct Learning Algorithms for L2 Support Vector Machines

Author:

Zigic Ljiljana,Kecman Vojislav

Publisher

Springer International Publishing

Reference16 articles.

1. Vapnik, V.: Estimation of Dependences Based on Empirical Data (in Russian), Nauka, Moscow (1979); (English translation: Springer Verlag, New York 1982)

2. Zigic, L., Strack, R., Kecman, V.: L2 SVM Revisited - Novel Direct Learning Algorithm and Some Geometric Insights. In: MENDEL 19th International Conference on Soft Computing, Brno, Czech Republic (2013)

3. Huang, T.M., Kecman, V., Kopriva, I.: Kernel Based Algorithms for Mining Huge Data Sets. In: Supervised, Semi- supervised, and Unsupervised Learning. Springer, Heidelberg (2006)

4. Abe, S.: Support Vector Machines for Pattern Classification, 2nd edn. Springer (2010)

5. Suykens, J., Vandewalle, J.: Least Squares Support Vector Machine Classifiers. Neural Processing Letters (NPL) 9(3), 293–300 (1999)

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