Stacking is a method used in various fields, including finance and data science, where multiple models or strategies are combined to improve overall performance. In finance, it often refers to layering different investment strategies to maximize returns while managing risk. In data science, stacking involves training several predictive models and then using another model to combine their predictions for better accuracy. In the context of machine learning, stacking typically involves a two-level approach. The first level consists of multiple base models, such as decision trees or neural networks, which generate predictions. The second level uses a meta-model to learn from these predictions and make the final decision, enhancing the overall predictive power.