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Boosting algorithms is one of the greatest tool in machine learning and over the years it has various versions and they all have their own identities. The main objective of the paper is to provide comprehensive study on various algorithms and try to solve a challenging classification problem of customer churn and observe the result of these algorithms too see which of them work the best in the raw state possible. In this paper of we used a dataset “Telecommunication Customer Churn Dataset” and we will few preprocessing to level the ground for all our models/algorithms. Finally we will run some test like accuracy, cross validation to find the best performing model among the boosting algorithm which we will use. [ABSTRACT FROM AUTHOR]