Capstone Project Đồ án tốt nghiệp Data Mining applications Prepaid churn model Decision trees Random Forest Support Vector Machine ROC R language
This paper evaluates different Machine Learning models which the aim to find out the good
algorithm for predicting churners in prepaid telecom industry. Several models have been used
and compared on the basis of different Data Mining methods and algorithm (Naïve Bayes, KNearest Neighbours, Decision Tree, Random Forest, and Support Vector Machine). To handle
the imbalance in the data, we use Receiver Operating Characteristics (ROC) curves to evaluate
the result beside the accuracy and churn rate. For the modeling examples we used RStudio
analysis tool and introduced the R language.