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High dimensional data classification and feature selection using support vector machines

Citations

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Cited by:

  1. Bottmer, Lea & Croux, Christophe & Wilms, Ines, 2022. "Sparse regression for large data sets with outliers," European Journal of Operational Research, Elsevier, vol. 297(2), pages 782-794.
  2. He Jiang, 2023. "Robust forecasting in spatial autoregressive model with total variation regularization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 195-211, March.
  3. Zhang, Yishi & Zhu, Ruilin & Chen, Zhijun & Gao, Jie & Xia, De, 2021. "Evaluating and selecting features via information theoretic lower bounds of feature inner correlations for high-dimensional data," European Journal of Operational Research, Elsevier, vol. 290(1), pages 235-247.
  4. Jimenez-Marquez, Jose Luis & Gonzalez-Carrasco, Israel & Lopez-Cuadrado, Jose Luis & Ruiz-Mezcua, Belen, 2019. "Towards a big data framework for analyzing social media content," International Journal of Information Management, Elsevier, vol. 44(C), pages 1-12.
  5. Jiang, He & Luo, Shihua & Dong, Yao, 2021. "Simultaneous feature selection and clustering based on square root optimization," European Journal of Operational Research, Elsevier, vol. 289(1), pages 214-231.
  6. Ni, Ji & Chen, Bowei & Allinson, Nigel M. & Ye, Xujiong, 2020. "A hybrid model for predicting human physical activity status from lifelogging data," European Journal of Operational Research, Elsevier, vol. 281(3), pages 532-542.
  7. Basna Mohammed Salih Hasan & Nawzat Sadiq Ahmed, 2021. "Feature selection technique applied in Medical application by Supervised algorithm: A Review," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 190-203.
  8. You-Shyang Chen & Ying-Hsun Hung & Yu-Sheng Lin, 2023. "A Study to Identify Long-Term Care Insurance Using Advanced Intelligent RST Hybrid Models with Two-Stage Performance Evaluation," Mathematics, MDPI, vol. 11(13), pages 1-34, July.
  9. Xie, Ying & Song, Dong-Ping & Dong, Jingxin & Feng, Yuanjun, 2025. "Predicting out-terminals for imported containers at seaports using machine learning: Incorporating unstructured data and measuring operational costs due to misclassifications," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 202(C).
  10. Subhadip Sarkar, 2023. "ABC classification using extended R-model, SVM and Lorenz curve," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1433-1455, September.
  11. Jiang, He & Tao, Changqi & Dong, Yao & Xiong, Ren, 2021. "Robust low-rank multiple kernel learning with compound regularization," European Journal of Operational Research, Elsevier, vol. 295(2), pages 634-647.
  12. Zhang, Yucheng & Xu, Shan & Zhang, Long & Yang, Mengxi, 2021. "Big data and human resource management research: An integrative review and new directions for future research," Journal of Business Research, Elsevier, vol. 133(C), pages 34-50.
  13. Goodell, John W. & Ben Jabeur, Sami & Saâdaoui, Foued & Nasir, Muhammad Ali, 2023. "Explainable artificial intelligence modeling to forecast bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 88(C).
  14. Jiménez-Cordero, Asunción & Morales, Juan Miguel & Pineda, Salvador, 2021. "A novel embedded min-max approach for feature selection in nonlinear Support Vector Machine classification," European Journal of Operational Research, Elsevier, vol. 293(1), pages 24-35.
  15. Víctor Blanco & Alberto Japón & Justo Puerto, 2020. "Optimal arrangements of hyperplanes for SVM-based multiclass classification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 175-199, March.
  16. Davila-Pena, Laura & García-Jurado, Ignacio & Casas-Méndez, Balbina, 2022. "Assessment of the influence of features on a classification problem: An application to COVID-19 patients," European Journal of Operational Research, Elsevier, vol. 299(2), pages 631-641.
  17. Herhausen, Dennis & Ludwig, Stephan & Abedin, Ehsan & Haque, Nasim Ul & de Jong, David, 2025. "From words to insights: Text analysis in business research," Journal of Business Research, Elsevier, vol. 198(C).
  18. Li, An-Da & He, Zhen & Wang, Qing & Zhang, Yang, 2019. "Key quality characteristics selection for imbalanced production data using a two-phase bi-objective feature selection method," European Journal of Operational Research, Elsevier, vol. 274(3), pages 978-989.
  19. Díaz, Verónica & Montoya, Ricardo & Maldonado, Sebastián, 2023. "Preference estimation under bounded rationality: Identification of attribute non-attendance in stated-choice data using a support vector machines approach," European Journal of Operational Research, Elsevier, vol. 304(2), pages 797-812.
  20. He Jiang & Weihua Zheng, 2022. "Deep learning with regularized robust long‐ and short‐term memory network for probabilistic short‐term load forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1201-1216, September.
  21. Gao, Renzhi & Yao, Xiaoyu & Wang, Zhao & Abedin, Mohammad Zoynul, 2024. "Sentiment classification of time-sync comments: A semi-supervised hierarchical deep learning method," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1159-1173.
  22. Jing Xiao & Wenfeng Zhu, 2025. "Data-Driven Personalized Individual Semantic Space Learning Methods for Linguistic Multi-attribute Group Decision Making," Group Decision and Negotiation, Springer, vol. 34(5), pages 1211-1233, October.
  23. Jiapeng Liu & Miłosz Kadziński & Xiuwu Liao & Xiaoxin Mao, 2021. "Data-Driven Preference Learning Methods for Value-Driven Multiple Criteria Sorting with Interacting Criteria," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 586-606, May.
  24. Liangjun Wu & Lihui Yang & Yabin Li & Jian Shi & Xiaochen Zhu & Yan Zeng, 2024. "Evaluation of the Habitat Suitability for Zhuji Torreya Based on Machine Learning Algorithms," Agriculture, MDPI, vol. 14(7), pages 1-17, July.
  25. Kusunoki, Yoshifumi & Tatsumi, Keiji, 2025. "Multi-class support vector machine based on minimization of reciprocal-geometric-margin norms," European Journal of Operational Research, Elsevier, vol. 324(2), pages 580-589.
  26. Gambella, Claudio & Ghaddar, Bissan & Naoum-Sawaya, Joe, 2021. "Optimization problems for machine learning: A survey," European Journal of Operational Research, Elsevier, vol. 290(3), pages 807-828.
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