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. Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case. 2002) have performed a comprehensive evaluation of the impact of SMOTE- based up-sampling. Chawla et al.,
136 
Let's personalize your content