Machine learning-based unified models for predicting drug clearance from pharmacokinetic animal and study design variables
Fig 3
Distribution of datasets selected for the prediction models, (A) imbalanced, (B) undersampling, (C) oversampling, and (D) simultaneous resampling methods.
Compared to Fig 3A, figures B, C, and D attain a well-balanced data distribution by modifying the frequency of data samples. This is accomplished by either decreasing or increasing the number of samples, using the Imbalanced-Learn Python Module.