Multi-view twin random vector functional link for classification problems

Jyoti Maurya

doi:10.1016/j.asoc.2026.116097

Multi-view twin random vector functional link for classification problems

2026-07-28

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DOI：10.1016/j.asoc.2026.116097

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• Propose a novel multi-view twin RVFL (MvTRVFL) which can potentially achieve better generalization performance. • MvTRVFL enhances the robustness of the model to noise and missing data in individual views. • We provide rigorous mathematical frameworks for MvTRVFL, leveraging the TRVFL topology. • Extensive experiments on various UCI repository datasets have been performed to validate the effectiveness of our proposed model.

Multi-view twin random vector functional link for classification problems

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