Ensemble Learning

Ensemble Learning is a machine learning method that improves predictive performance by combining multiple learners. Its core objective is to enhance the overall model's generalization ability and stability by integrating predictions from multiple models, thereby reducing the variance and bias of a single model. In the field of computer vision, Ensemble Learning is widely applied to tasks such as image classification and object detection, significantly improving the accuracy and robustness of algorithms.