A novel algorithm for classification using a low rank approximation of kernel-based support vector machines with applications-Reference-Cited by-同舟云学术

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A novel algorithm for classification using a low rank approximation of kernel-based support vector machines with applications

Published:2023-07-28 Issue: Volume: Page:1-21
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Chatrabgoun O.¹²,Esmaeilbeigi M.³,Daneshkhah A.¹⁴,Kamandi A.⁵,Salimi N.⁶

Affiliation:

1. School of Computing, Electronics and Mathematics, Coventry University, Coventry, UK

2. Department of Statistics, Faculty of Mathematical Sciences & Statistics, Malayer University, Malayer, Iran

3. Department of Mathematics, Faculty of Mathematical Sciences & Statistics, Malayer University, Malayer, Iran

4. Research Centre for Computational Science and Mathematical Modelling, Coventry University, Coventry, UK

5. Department of Mathematics, University of Science and Technology of Mazandaran, Behshahr, Iran

6. Department of Computer Engineering, Faculty of Engineering, Arak University, Arak, Iran

Publisher

Informa UK Limited

Subject

Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2023.2236816

Reference37 articles.

1. A morphological neural network for binary classification problems

2. Robust twin bounded support vector machines for outliers and imbalanced data

3. Predicting Primary Sequence-Based Protein-Protein Interactions Using a Mercer Series Representation of Nonlinear Support Vector Machine

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