Analysis of Mobile Operator Customers with Machine Learning Techniques

In this study, churn analysis of mobile operators is applied on a data set obtained with the participation of different mobile operator users in Turkey. We also classify the mobile users according to their mobile operators by using machine learning techniques. We use Decision Trees, K-nearest neighbors, Support Vector Machines, Logistic Regression, Naive Bayes, Artificial Neural Network classification algorithms and Gradient Boosting, Random Forests, Adaboost and Maximum Voting ensemble learning algorithms. As a result, we see that the best performance classification results are obtained by maximum voting method and all results are interpreted and shared.