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Risk control modeling framework(风控建模工具集)

声明:工具箱为风控建模过程提供支持,因工作紧迫暂于23Feb19停更;感谢jiangchao8@jd & huyao3@jd为这些积累提供若干支持

最新Note:

  • 整个工具箱已做完re-view:包括每个模块其他语言的double-check、每个模块参数名称标准化
  • 2.2.2 Chi2_merge.py模块可以使用,但还需修改
  • Example.x为测试实例,可参照(!!实际项目中的特征名和数据等保密信息已做处理!!)
  • Pypi:https://pypi.org/project/rcmf/

需更新:

  • 特征筛选部分没有落地,仍在整理中,包括:集成模型筛选方法、逻辑回归L1正则化
  • vintage、迁移率、pmml等
  • 3个使用示例最好生成MD,增加可读性
  • 2.2.2 Chi2_merge.py:去除卡方分箱的“最优分箱组数”判定,添加卡方值阈值约束
  • 特征筛选:逐步回归

更新日志:

29Dec2018

  • 添加特征筛选部分(2.x):包含特征稳定性(PSI from *Yao)、特征共线性(方差膨胀因子和相关性矩阵)
    1. Data_Explore.py:去除相关性矩阵、对分布图拼接按照4维或9维子图展示
  • 4.1 Model performance.py:添加准召图

更新日志:

13Jan2019

  • 2.2.2 Cut_merge.py:① 优化分箱过程,直接从pd.cut解析结果; ② 优化从分箱数据集至WOE数据集的映射逻辑; ③ 将WOE计算并入分箱程序
  • 4.1 Model performance.py:① 利用sklearn中混淆矩阵函数加快计算; ② 添加3线图(准确率、召回率、F1-Score)

更新日志:

25Jan2019

  • 2.x Collinearity.py:相关性计算部分的热力图展示,可以控制哪些特征用于绘图;例如可以abs(corr) > 0.8的特征,或者是按相关性排序后取前20个特征
  • 3.x PDO_Score_Convert.py:放活odds定义,如不定义,则按照如下规则计算:对train数据集计算ks切点,取切点的百分位点区间内的所有y_label,计算好坏比
  • RCMF使用说明:完成初版

更新日志:

10Jun2019

  • 已为全部脚本更新help
    1. Data_Explore.py:更新计算方式,更新数值型特征的自定义分布,更新伪字符型变量(99%都是数值的字符型变量)分布探索

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