Support Vector Machines with the Ramp Loss and the Hard Margin Loss
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DOI: 10.1287/opre.1100.0854
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References listed on IDEAS
- J. Brooks & Eva Lee, 2010. "Analysis of the consistency of a mixed integer programming-based multi-category constrained discriminant model," Annals of Operations Research, Springer, vol. 174(1), pages 147-168, February.
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Cited by:
- Jian Luo & Shu-Cherng Fang & Zhibin Deng & Xiaoling Guo, 2016. "Soft Quadratic Surface Support Vector Machine for Binary Classification," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(06), pages 1-22, December.
- Blanquero, R. & Carrizosa, E. & Jiménez-Cordero, A. & Martín-Barragán, B., 2019. "Functional-bandwidth kernel for Support Vector Machine with Functional Data: An alternating optimization algorithm," European Journal of Operational Research, Elsevier, vol. 275(1), pages 195-207.
- Baldomero-Naranjo, Marta & Martínez-Merino, Luisa I. & Rodríguez-Chía, Antonio M., 2020. "Tightening big Ms in integer programming formulations for support vector machines with ramp loss," European Journal of Operational Research, Elsevier, vol. 286(1), pages 84-100.
- J. Paul Brooks & Eva K. Lee, 2014. "Solving a Multigroup Mixed-Integer Programming-Based Constrained Discrimination Model," INFORMS Journal on Computing, INFORMS, vol. 26(3), pages 567-585, August.
- Xianning Wang & Zhengang Ma & Jingrong Dong, 2021. "Quantitative Impact Analysis of Climate Change on Residents’ Health Conditions with Improving Eco-Efficiency in China: A Machine Learning Perspective," IJERPH, MDPI, vol. 18(23), pages 1-23, December.
- Pietro Belotti & Pierre Bonami & Matteo Fischetti & Andrea Lodi & Michele Monaci & Amaya Nogales-Gómez & Domenico Salvagnin, 2016. "On handling indicator constraints in mixed integer programming," Computational Optimization and Applications, Springer, vol. 65(3), pages 545-566, December.
- Mohammad Poursaeidi & O. Kundakcioglu, 2014. "Robust support vector machines for multiple instance learning," Annals of Operations Research, Springer, vol. 216(1), pages 205-227, May.
- Jin Xiao & Yuhang Tian & Yanlin Jia & Xiaoyi Jiang & Lean Yu & Shouyang Wang, 2023. "Black-Box Attack-Based Security Evaluation Framework for Credit Card Fraud Detection Models," INFORMS Journal on Computing, INFORMS, vol. 35(5), pages 986-1001, September.
- Xianning Wang & Zhengang Ma & Jiusheng Chen & Jingrong Dong, 2023. "Can Regional Eco-Efficiency Forecast the Changes in Local Public Health: Evidence Based on Statistical Learning in China," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
- Pedro Duarte Silva, A., 2017. "Optimization approaches to Supervised Classification," European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
- Carrizosa, Emilio & Nogales-Gómez, Amaya & Romero Morales, Dolores, 2017. "Clustering categories in support vector machines," Omega, Elsevier, vol. 66(PA), pages 28-37.
- Zhou, Jingke & Zhu, Lixing, 2016. "Principal minimax support vector machine for sufficient dimension reduction with contaminated data," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 33-48.
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Keywords
statistics; pattern analysis; support vector machines; programming; integer applications; quadratic integer programming;All these keywords.
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