Accurate estimates of the generalization ability for symmetric set of predictors and randomized learning algorithms-Reference-Cited by-同舟云学术

Accurate estimates of the generalization ability for symmetric set of predictors and randomized learning algorithms

Published:2010-09 Issue:3 Volume:20 Page:241-250
ISSN:1054-6618
Container-title:Pattern Recognition and Image Analysis
language:en
Short-container-title:Pattern Recognit. Image Anal.

Author:

Frei A. I.

Publisher

Pleiades Publishing Ltd

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition

Link

http://link.springer.com/content/pdf/10.1134/S1054661810030016.pdf

Reference7 articles.

1. V. N. Vapnik and A. Ya. Chervonenko, Pattern Recognition Theory (Moscow, Nauka, 1974) [in Russian].

2. V. Vapnik, Statistical Learning Theory (New York, Wiley, 1998).

3. K. V. Vorontsov, “Accurate Estimates of Overtraining Probability,” Doklady RAN, 429(1), 15–18 (2009).

4. K. V. Vorontsov, “Combinatorial Approach to Overtraining,” All-Russian Conference on Mathematical Methods of Pattern Recognition-14 (Moscow, MAKS Press, 2009), pp. 18–21.

5. P. V. Botov, “Accurate Estimates of Overtraining Probability for Monotonic and Unimodal Families of Algorithms,” All-Russian Conference on Mathematical Methods of Pattern Recognition-14 (Moscow, MAKS Press, 2009), pp. 7–10.

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