Entropy-Based Fuzzy Least Squares Twin Support Vector Machine for Pattern Classification

Neural Processing Letters ◽

10.1007/s11063-019-10078-w ◽

2019 ◽

Vol 51 (1) ◽

pp. 41-66 ◽

Author(s):

Sugen Chen ◽

Junfeng Cao ◽

Fenglin Chen ◽

Bingbing Liu

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

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Multiclass Least Squares Twin Support Vector Machine for Pattern Classification

International Journal of Database Theory and Application ◽

10.14257/ijdta.2015.8.6.26 ◽

2015 ◽

Vol 8 (6) ◽

pp. 285-302 ◽

Author(s):

Divya Tomar ◽

Sonali Agarwal

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

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Simulated annealing least squares twin support vector machine (SA-LSTSVM) for pattern classification

Soft Computing ◽

10.1007/s00500-016-2067-4 ◽

2016 ◽

Vol 21 (15) ◽

pp. 4361-4373 ◽

Author(s):

Javad Salimi Sartakhti ◽

Homayun Afrabandpey ◽

Mohamad Saraee

Keyword(s):

Support Vector Machine ◽

Simulated Annealing ◽

Least Squares ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

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Capped L2,p-norm metric based robust least squares twin support vector machine for pattern classification

Neural Networks ◽

10.1016/j.neunet.2021.06.028 ◽

2021 ◽

Author(s):

Chao Yuan ◽

Liming Yang

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

Support Vector ◽

Robust Least Squares

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KNN-based least squares twin support vector machine for pattern classification

Applied Intelligence ◽

10.1007/s10489-018-1225-z ◽

2018 ◽

Vol 48 (12) ◽

pp. 4551-4564 ◽

Author(s):

A. Mir ◽

Jalal A. Nasiri

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

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Locality preserving projection least squares twin support vector machine for pattern classification

Pattern Analysis and Applications ◽

10.1007/s10044-018-0728-x ◽

2018 ◽

Vol 23 (1) ◽

pp. 1-13 ◽

Author(s):

Su-Gen Chen ◽

Xiao-Jun Wu ◽

Juan Xu

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

Support Vector ◽

Locality Preserving Projection ◽

Locality Preserving

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Robust Parametric Twin Support Vector Machine for Pattern Classification

Neural Processing Letters ◽

10.1007/s11063-017-9633-3 ◽

2017 ◽

Vol 47 (1) ◽

pp. 293-323 ◽

Author(s):

Reshma Rastogi ◽

Sweta Sharma ◽

Suresh Chandra

Keyword(s):

Support Vector Machine ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

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Multi-category laplacian least squares twin support vector machine

Applied Intelligence ◽

10.1007/s10489-016-0770-6 ◽

2016 ◽

Vol 45 (2) ◽

pp. 458-474 ◽

Author(s):

Reshma Khemchandani ◽

Aman Pal

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Twin Support Vector Machine ◽

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Fast Laplacian twin support vector machine with active learning for pattern classification

Applied Soft Computing ◽

10.1016/j.asoc.2018.10.042 ◽

2019 ◽

Vol 74 ◽

pp. 424-439 ◽

Author(s):

Reshma Rastogi ◽

Sweta Sharma

Keyword(s):

Support Vector Machine ◽

Active Learning ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

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Twin support vector machine based on adjustable large margin distribution for pattern classification

International Journal of Machine Learning and Cybernetics ◽

10.1007/s13042-020-01124-4 ◽

2020 ◽

Vol 11 (10) ◽

pp. 2371-2389

Author(s):

Liming Liu ◽

Maoxiang Chu ◽

Yonghui Yang ◽

Rongfen Gong

Keyword(s):

Support Vector Machine ◽

Pattern Classification ◽

Twin Support Vector Machine ◽

Support Vector ◽

Large Margin ◽

Margin Distribution

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Leak Detection and Location of Pipelines Based on LMD and Least Squares Twin Support Vector Machine

IEEE Access ◽

10.1109/access.2017.2703122 ◽

2017 ◽

Vol 5 ◽

pp. 8659-8668 ◽

Author(s):

Xianming Lang ◽

Ping Li ◽

Zhiyong Hu ◽

Hong Ren ◽

Yan Li

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Leak Detection ◽

Twin Support Vector Machine ◽

Support Vector ◽

Leak Detection And Location

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