Jul 1, 2024 · Class imbalance is sometimes considered a problem when developing clinical prediction models and assessing their performance. But how reliable are these predictions when they’re based on … Nov 21, 2024 · Oversampling can boost model performance in imbalanced datasets but runs the risk of overfitting, while non-oversampling methods like undersampling or class weighting can help avoid... Dec 20, 2023 · We argue in the following editorial the issues with oversampling that stem from the possibility of overfitting and the generation of synthetic cases that might not accurately represent the... Feb 25, 2025 · Handling imbalanced datasets is crucial for building robust and reliable machine learning models. Various sampling techniques—oversampling, undersampling, and hybrid methods—help … Mar 23, 2025 · In this research, we aim to present a comprehensive review of recent resampling approaches developed to handle class imbalance through a data-centric lens.
