基于集成学习的中国P2P网络借贷信用风险预警模型的对比研究*
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操玮, 李灿, 贺婷婷, 朱卫东
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Predicting Credit Risks of P2P Loans in China Based on Ensemble Learning Methods
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Cao Wei,Li Can,He Tingting,Zhu Weidong
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| 表8 平均Type-I error(%) |
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训练
测试比 | Bagging | Boosting | Random Subspace | Rotation Forest | | A | FS | A | FS | A | FS | A | FS | | 60:40 | 8.16 | 5.36 | 6.78 | 3.91 | 8.96 | 5.98 | 4.94 | 1.61 | | 70:30 | 8.10 | 4.00 | 7.24 | 3.27 | 10.62 | 4.31 | 5.17 | 2.07 | | 80:20 | 8.78 | 5.13 | 9.51 | 4.88 | 14.14 | 9.27 | 6.58 | 1.45 | | 平均值 | 8.35 | 4.82 | 7.84 | 4.02 | 11.24 | 6.52 | 5.56 | 1.71 |
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