Four Oversampling and Under-Sampling Methods for Imbalanced Classification Using Python

Amy @GrabNGoInfo
GrabNGoInfo
Published in
13 min readFeb 19, 2022

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Random Oversampling, SMOTE, Random Under-sampling, and NearMiss

Four Oversampling and Under-Sampling Methods for Imbalanced Classification Using Python. Random Oversampling, SMOTE, Random Under-sampling, and NearMiss
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Oversampling and under-sampling are the techniques to change the ratio of the classes in an imbalanced modeling dataset. This step-by-step tutorial explains how to use oversampling and under-sampling in the Python imblearn library to adjust the…

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