tjhznb666 / Predicting-future-customer-credit-risk-based-on-machine-learning-algorithmView on GitHub
利用python对3000个数据利用机器学习算法建立模型，并预测未来客户信用风险。处理数据不均衡问题时采用了SMOTE过采样以及随机过采样技术；通过相关性分析进行特征选择；建模过程中用到了Logistic回归、SVM、随机森林、GBDT四种模型，并通过网格搜索法确定最优参数；利用准确率、KS值、ROC曲线、AUC值以及lift曲线进行模型评估。
☆36Jun 8, 2022Updated 3 years ago
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