Supervised learning models in the predictive maintenance field are regularly trained on highly imbalanced industrial datasets: machine failures occur rarely but have a disproportionate effect on operations. In addition to the clear class disparity, failure data are typically non-homogeneous, with different failure modes arising from distinct physical processes and exhibiting a multimodal distribution across minorities and classes.
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By Yicheng Kang, Yuling Jiao, Xin Geng, Mahesh Nagarajan
arXiv:2607. 19153v1 Announce Type: cross Abstract: Supervised learning models in the predictive maintenance field are regularly trained on highly imbalanced industrial datasets: machine failures occur rarely but have a disproportionate effect on operations.
By Alexis Lazanas, Georgios Kampouropoulos
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By Mohammed Ayalew Belay, Lucas Ferreira Bernardino, Adil Rasheed, Rub\'en M. Monta\~n\'es, Pierluigi Salvo Rossi
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