Semisupervised Feature Selection via Structured Manifold Learning

Recently, semisupervised feature selection has gained more attention in many real applications due to the high cost of obtaining labeled data. However, existing methods cannot solve the ``multimodality'' problem that samples in some classes lie in several separate clusters. To solve the mu...

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Veröffentlicht in:	IEEE transactions on cybernetics 2022-07, Vol.PP (7), p.1-11
Hauptverfasser:	Chen, Xiaojun, Chen, Renjie, Wu, Qingyao, Nie, Feiping, Yang, Min, Mao, Rui
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Clusters Feature extraction Feature selection Iterative methods Laplace equations local structure learning Machine learning Manifold learning Manifolds Manifolds (mathematics) Optimization semisupervised feature selection structure learning Task analysis Training Training data
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