Constrained feature weighting for semi-supervised learning
Author:
Funder
Natural Science Research of Jiangsu Higher Education Institutions of China
Six Talent Peaks Project in Jiangsu Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05691-9.pdf
Reference39 articles.
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2. Bouchlaghem Y, Akhiat Y, Amjad S (2022) Feature selection: A review and comparative study. E3S Web of Conferences 351:01046
3. Pang Q, Zhang L (2020) Semi-supervised neighborhood discrimination index for feature selection. Knowl-Based Syst 204:106224
4. Chen H, Chen H, Li W, Li T, Luo C, Wan J (2022) Robust dual-graph regularized and minimum redundancy based on self-representation for semi-supervised feature selection. Neurocomputing 490:104–123
5. Jin L, Zhang L, Zhao L (2023) Max-difference maximization criterion: A feature selection method for text categorization. Front Comp Sci 17(1):171337
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