PML-FSMIR reconstructs candidate labels with a mutual-information matrix and reweights selected features by label connectivity, scoring first on most benchmark metrics in the reported experiments.
Multi-label feature selection with high-sparse personalized and low-redundancy shared common features.Information Processing & Management, 61(3):103633,
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Noise-Resistant Label Reconstruction Feature Selection for Partial Multi-Label Learning
PML-FSMIR reconstructs candidate labels with a mutual-information matrix and reweights selected features by label connectivity, scoring first on most benchmark metrics in the reported experiments.