4 Oversampling and Undersampling Methods for Imbalanced Classification Using Python
9:33
YouTubeGrab N Go Info
4 Oversampling and Undersampling Methods for Imbalanced Classification Using Python
Random Oversampling, SMOTE, Random Under-Sampling, and Near Miss Under-Sampling are four widely used sampling 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 Python using imblearn library to adjust the imbalanced classes for ...
10.5K views1 Oct 2021
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