Supervised incremental feature selection using regularization vector for dynamic multi-scale interval valued datasets

Zihan Feng

doi:10.1016/j.patcog.2025.111985

Supervised incremental feature selection using regularization vector for dynamic multi-scale interval valued datasets

2025-06-23

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Zihan Feng

张晓艳 (Xiaoyan Zhang)

DOI：10.1016/j.patcog.2025.111985

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• The paper first establishes the concepts of object affiliation relation and class. • We provide a theoretical basis for integrating replay and regularization. • Regularization and replay strategies is realized within dynamic environments. • Empirical results show that the method significantly outperforms conventional techniques.

Supervised incremental feature selection using regularization vector for dynamic multi-scale interval valued datasets

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