Ensemble Learning
ABOUT
Ensemble learning is a machine learning method combining multiple learning algorithms. An ensemble contains a number of base learners trying to solve the same problem. The base learning algorithm generating the base learners from training data can be a decision tree, a neural network or other kinds of machine learning algorithms. Whereas ordinary machine learning approaches try to learn one hypothesis, ensemble learning systems combine different hypotheses. In this way, ensembles usually have better generalisation results than base learners.
RESOURCES
Zhou, Z. H. (2015). Ensemble learning. Encyclopedia of biometrics, 411-416.
Zhou Zhihua (2012). Ensemble Methods: Foundations and Algorithms. Chapman and Hall/CRC
Robert Schapire; Yoav Freund (2012). Boosting: Foundations and Algorithms. MIT.
