Robust correlation feature selection based support vector machine approach for high dimensional datasets
Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. In application, the presence of anomalous observations in both predictors and responses can seriously jeopardize...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Elsevier B.V.
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/120119/1/120119.pdf http://psasir.upm.edu.my/id/eprint/120119/ https://linkinghub.elsevier.com/retrieve/pii/S2666720725000943 |
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