2002, Data mining, Testing and Visualization

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

MAY 20, 2021

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. Their tests are performed using C4.5-generated Generation of artificial examples. Chawla et al.,

Machine Learning

Machine Learning Metrics Data mining Knowledge Discovery

Data Leaders Brief

ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Webinars

Stay Connected