Churn Prediction for Game Industry Based on Cohort Classification Ensemble

Tsymbalov, Evgenii (2016): Churn Prediction for Game Industry Based on Cohort Classification Ensemble. Published in: CEUR Workshop Proceeding , Vol. 1627, No. Experimental Economics and Machine Learning (25 July 2016): pp. 94-100.

Abstract

In this paper, we present a cohort-based classification approach to the churn prediction for social on-line games. The original metric is proposed and tested on real data showing a good increase in revenue by churn preventing. The core of the approach contains such components as tree-based ensemble classifiers and threshold optimization by decision boundary.

• Item Type: MPRA Paper
• Language: English
• Keywords: Churn prediction, ensemble classification, cohort-based prediction, on-line games, game analytics
• Subjects: C - Mathematical and Quantitative Methods > C9 - Design of Experiments > C91 - Laboratory, Individual Behavior; L - Industrial Organization > L8 - Industry Studies: Services > L86 - Information and Internet Services ; Computer Software

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