👉 In the context of data analysis and machine learning, "outperforming" refers to achieving or surpassing an existing benchmark or standard. This means that a model is expected to perform better than another one in terms of accuracy, performance, or any other objective criterion. It could be measured through various metrics like precision, recall, F1-score, area under the curve (AUC), etc., as these are commonly used for evaluating machine learning models' performance on different datasets and scenarios.