A bipartite matching-based feature selection for multi-label learning

Many real-world data have multiple class labels known as multi-label data, where the labels are correlated with each other, and as such, they are not independent. Since these data are usually high-dimensional, and the current multi-label feature selection methods have not been precise enough, then a...

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Veröffentlicht in:International journal of machine learning and cybernetics 2021-02, Vol.12 (2), p.459-475
Hauptverfasser: Hashemi, Amin, Dowlatshahi, Mohammad Bagher, Nezamabadi-Pour, Hossein
Format: Artikel
Sprache:eng
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