ML internals: Synthetic Minority Oversampling (SMOTE) Technique
Domino Data Lab
MAY 20, 2021
Machine Learning algorithms often need to handle highly-imbalanced datasets. In their 2002 paper Chawla et al. Learning wider regions improves the generalisation of the classifier, as the region of the minority class is not so tightly constrained by the observations in the majority. Generation of artificial examples.
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