Nov 12, 2020 · In this paper, an algorithm named Label Correlation based K-Nearest Neighbor (LC-KNN) method is proposed through analyzing and weighting the ...
The experimental results on the natural scene dataset show that the LC-KNN algorithm is significantly better than mainstream multi-label learning algorithms ...
A Natural Scene Recognition Learning Based on Label Correlation
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The experimental results on the natural scene dataset show that the LC-KNN algorithm is significantly better than mainstream multi-label learning algorithms ...
Duration: 0:52
Posted: Dec 8, 2022
Posted: Dec 8, 2022
Jan 25, 2023 · We introduce an alternative multi-label feature learning solution that incorporates both labeled and unlabeled information.
Aug 30, 2024 · We propose an oversampling method called Multi-Label Oversampling with Natural neighbor and label Correlation (MLONC).
Label Distribution Learning is a novel machine learning paradigm that assigns label distribution to each instance. Numerous LDL methods proposed.
MUCO explicitly and effectively learns the latent label correlations by updating a label correlation tensor, which provides highly accurate and interpretable ...
In multi-label data, labels are not independent; there are correlations between them. Utilizing label correlations effectively is a key means of improving MLC ...
In this paper, we pro- pose a novel framework for multi-label classification, High- order Tie-in Variational Autoencoder (HOT-VAE), which per- forms adaptive ...