Boosting is a kind of ensemble methods which produce a strong learner that is capable of making very accurate predictions by combining rough and moderately inaccurate learners (which are called as base learners or weak learners). In particular, Boosting sequentially trains a series of base learners by using a base learning algorithm, where the training examples wrongly predicted by a base learn...