Ensemble Learning

Ensemble Learning is a machine learning method that enhances predictive performance by combining multiple learners. Its core objective is to improve the model's generalization ability and stability by integrating diverse learners, thereby reducing the risk of overfitting. In practical applications, Ensemble Learning is widely used in fields such as classification, regression, and feature selection, effectively improving the efficiency and accuracy of solving complex problems.