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Supervised incremental feature selection using regularization vector for dynamic multi-scale interval valued datasets
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AI
DOI：10.1016/j.patcog.2025.111985.png)
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Abstract
En 中文
• 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.
Journal
IF:
7.6
Papers:
1.4W
Citations:
4.5W
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PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
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