October 2017
Beginner to intermediate
572 pages
26h 1m
English
Similar to the bagging method, boosting starts with a simple or weak classifier and gradually improves it by reweighting the misclassified samples. Thus, the new classifier can learn from previous classifiers. The adabag package provides implementation of the AdaBoost.M1 and SAMME algorithms. Therefore, one can use the boosting method in adabag to perform ensemble learning. In this recipe, we will use the boosting method in adabag to classify the telecom churn dataset.
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