Adaptive discriminant analysis for semi-supervised feature selection

DOI10.1016/j.ins.2021.02.035zbMath1527.68203OpenAlexW3134157553MaRDI QIDQ6086306

Feiping Nie, Joshua Zhexue Huang, Weichan Zhong, Xiaojun Chen

Publication date: 9 November 2023

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2021.02.035

zbMATH Keywords

discriminant analysisfeature selectionsemi-supervised feature selection

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (5)

Unsupervised feature selection via adaptive autoencoder with redundancy control ⋮ Robust multi-view learning via adaptive regression ⋮ Convolution-based linear discriminant analysis for functional data classification ⋮ Adaptive graph learning for semi-supervised feature selection with redundancy minimization ⋮ Label correlations variation for robust multi-label feature selection

Cites Work

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• Online streaming feature selection using rough sets
• A factor graph model for unsupervised feature selection
• Ensemble feature selection using election methods and ranker clustering
• Feature grouping and selection: a graph-based approach
• Learning a discriminant graph-based embedding with feature selection for image categorization

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