Ensemble Learning Zhi-Hua Zhou National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China zhouzh@nju.edu.cn Synonyms Committee-based learning; Multiple classifier systems; Classifier combination Definition Ensemble learning is a machine learning paradigm where multiple learners are trained to solve the same problem. In contrast to ordinary machine learning approaches which try to learn one hypothesis from training data, ensemble methods try to construct a set of hypotheses and combine them to use. Main Body Text Introduction An ensemble contains a number of learners which are usually called base learners. The generalization ability of an ensemble is usually much stronger than that of base learners. Actually, ensemble learning is appealing because that it is able to boost weak learners which are slightly better than random guess to strong learners which can make very accurate predictions. So, “base learners” are also referred as “weak
