Identifying Key Learning Algorithm Parameter of Forward Feature Selection to Integrate with Ensemble Learning for Customer Churn Prediction
Sabahat Tasneem,
Muhammad Younas,
Qasim Shafiq
Abstract:The Telecommunication has been facing fierce growth of customer data and competition in the market for a couple of decades. Due to this situation, an analytical strategy of proactive anticipation about customer churn and their profitable retention is inevitable for Telecommunication companies. To nip this problem in the bud, a lot of research work has been conducted in the past, but still the previously introduced churn prediction models possess their own limitations, such as high dimensional data with poor in… Show more
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