A dataset in which class labels are not evenly distributed, meaning one class has significantly more examples than others. this imbalance can cause machine learning models to favor the majority class and leads to poor performance on the minority class. https://developers.google.com/machine-learning/crash-course/overfitting/imbalanced-datasets