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7 平均准确率(%) |
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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 | 97.29 | 98.34 | 97.51 | 98.52 | 95.88 | 97.51 | 98.40 | 99.39 | | 70:30 | 97.79 | 98.81 | 97.71 | 98.92 | 97.01 | 97.84 | 98.43 | 99.30 | | 80:20 | 96.97 | 98.70 | 96.76 | 97.89 | 95.95 | 97.44 | 98.10 | 99.27 | | 平均值 | 97.35 | 98.62 | 97.32 | 98.44 | 96.27 | 97.60 | 98.31 | 99.32 |
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