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Model Optimization in Imbalanced Regression. (arXiv:2206.09991v2 [cs.LG] UPDATED)
Aug. 17, 2022, 1:11 a.m. | Aníbal Silva, Rita P. Ribeiro, Nuno Moniz
stat.ML updates on arXiv.org arxiv.org
Imbalanced domain learning aims to produce accurate models in predicting
instances that, though underrepresented, are of utmost importance for the
domain. Research in this field has been mainly focused on classification tasks.
Comparatively, the number of studies carried out in the context of regression
tasks is negligible. One of the main reasons for this is the lack of loss
functions capable of focusing on minimizing the errors of extreme (rare)
values. Recently, an evaluation metric was introduced: Squared Error Relevance …
More from arxiv.org / stat.ML updates on arXiv.org
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