A novel tree-based dynamic heterogeneous ensemble method for credit scoring

•A tree-based heterogeneous ensemble credit scoring model is proposed.•Advanced GBDT-based methods function as components of our proposal.•An overfitting-cautious ensemble selection strategy is developed.•Our proposal outperforms the benchmark models significantly in most cases.•Our proposal is robu...

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Veröffentlicht in:	Expert systems with applications 2020-11, Vol.159, p.113615, Article 113615
Hauptverfasser:	Xia, Yufei, Zhao, Junhao, He, Lingyun, Li, Yinguo, Niu, Mengyi
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Benchmarks Computational efficiency Computing costs Credit scoring Gradient boosting decision tree Machine learning Random forests Selective ensemble State-of-the-art reviews
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