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A Framework for Multi-Label Learning Using Label Ranking and Correlation
2015Multi-relational data mining is a rapidly growing area used for mining relational databases. While traditional data mining approaches search patterns in a single data table, relational data mining techniques look for patterns which exist in multiple tables. Multi-label learning (classification) comes under multi-relational data mining technique.
Malik Irfan Shaukat, Muhammad Usman 0005
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Multi-Label Adversarial Attack Based on Label Correlation
2023 IEEE International Conference on Image Processing (ICIP), 2023Mingzhi Ma +5 more
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Label correlations variation for robust multi-label feature selection
Information Sciences, 2022Wanfu Gao, Yonghao Li
exaly
Correlation of Efficiency of Labeling with Chemical Constitution
1963The Wilzbach technique for tritium labeling has become an established method for the labeling of organic compounds. However, the prediction of the extent of tritium incorporation in various types of compounds is still conjectural. Since many hundreds of compounds have been labeled in this fashion, a large amount of information appears to be available ...
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Multi-label feature selection based on label correlations and feature redundancy
Knowledge-Based Systems, 2022Weiyao Lan, Wei Weng, Yuling Fan
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Invariant Correlation of Representation With Label
IEEE Transactions on Information Forensics and SecurityGaojie Jin +4 more
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Label distribution feature selection with feature weights fusion and local label correlations
Knowledge-Based Systems, 2022Wenbin Qian
exaly
Global and Adaptive Local Label Correlation for Multi-label Learning with Missing Labels
2023 International Joint Conference on Neural Networks (IJCNN), 2023Qingxia Jiang +3 more
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Multi-label feature selection with local discriminant model and label correlations
Neurocomputing, 2021Wei Weng, Yuling Fan, Shunxiang Wu
exaly

