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Tree-based machine learning classifiers outperform linear, instance-based, Bayesian, and function-based models for customer churn prediction, and their susceptibility to class imbalance can be effectively mitigated by combining data sampling with homogeneous ensemble methods. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Empirical analysis of tree-based classification models for customer churn prediction

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