Erna Dwiyanti

Handling Imbalanced Data in Churn Prediction Using RUSBoost and Feature Selection (Case Study: PT.Telekomunikasi Indonesia Regional 7)

2016 · Advances in intelligent systems and computing

Solving imbalance problems is a challenging tasks in data mining and machine learning. Most classifiers are biased towards the majority class examples when learning from highly imbalanced data. In practice, churn prediction is considered as …