DataMiningCase:基于真实业务上手数据挖掘(银行流失预警)

上传者: 42131276 | 上传时间: 2022-12-25 17:03:57 | 文件大小: 27.72MB | 文件类型: ZIP
DataMiningCase 流失预警模型(二分类),代码原型为本人在某银行做的流失模型,AUC:83%、召回率(覆盖率):19.4%,精确率:85%(数据是外部数据/代码已脱敏) 基于真实业务上手数据挖掘(银行流失预警):数据的处理、LightGBM、sklearn包(里面含有:GridSearchCV寻找最优参、StratifiedKFold分层5折切分、train_test_split单次数据切分等)、stacking模型融合、画AUC图、画混淆矩阵图,并输出预测名单。 告诉你:是什么(WHAT)、怎么做(HOW)、为什么这么做(WHY)。 注释覆盖率为80%左右,旨在帮助快速入门,新手级 项目涉及的如下: 商业理解 数据理解 数据处理(数据准备) 特征工程(数据准备) 正负样本特征线性图 RFECV(特征五折递归消除) Importan

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