Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels-Reference-Cited by-同舟云学术

Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels

Published:2016-08 Issue: Volume:80 Page:53-66
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Utkin Lev V.,Chekh Anatoly I.,Zhuk Yulia A.

Funder

RFBR

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference53 articles.

1. Support vector machines for interval discriminant analysis;Angulo;Neurocomputing,2008

2. Antonucci, A., de Rosa, R., Giusti, A., & Cuzzolin, F. (2013). Temporal data classification by imprecise dynamical models. In Proc. of the 8th international symposium on imprecise probability: Theories and applications (pp. 13–22).

3. Solving interval linear systems with linear programming techniques;Beaumont;Linear Algebra and its Applications,1998

4. Chance constrained uncertain classification via robust optimization;Ben-Tal;Mathematical Programming, Series B,2011

5. Robust optimization;Ben-Tal,2009

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