What is an Ensemble Method? The ensemble is a method used in the machine learning algorithm. In this method, multiple models or ‘weak learners’ are trained to rectify the same problem and integrated to gain desired results. Weak models combined rightly give accurate models. Bagging Bagging is an acronym for ‘Bootstrap Aggregation’ and is used to decrease the variance in the prediction model. Bagging is a parallel method that fits different, considered learners independently from each other, making it possible to train them simultaneously. Bagging generates additional data for training from the dataset. This is achieved by random sampling with replacement from the original dataset. Sampling with replacement may repeat some observations in each new training data set. Every element in Bagging is equally probable for appearing in a new dataset. These multi datasets are used to train multiple models in parallel. The average of all the predictions from different ensemble models i...