feature_utils.py 1.1 KB

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  1. # -*- coding:utf-8 -*-
  2. """
  3. @author: yq
  4. @time: 2023/12/28
  5. @desc: 特征工具类
  6. """
  7. import pandas as pd
  8. from sklearn.preprocessing import KBinsDiscretizer
  9. from entitys import DataSplitEntity
  10. from enums import BinsStrategyEnum
  11. def f_get_bins(data: DataSplitEntity, feat: str, strategy: str='quantile', nbins: int=10) -> pd.DataFrame:
  12. # 等频分箱
  13. if strategy == BinsStrategyEnum.QUANTILE.value:
  14. kbin_encoder = KBinsDiscretizer(n_bins=nbins, encode='ordinal', strategy='quantile')
  15. feature_binned = kbin_encoder.fit_transform(data[feat])
  16. return feature_binned.astype(int).astype(str)
  17. # 等宽分箱
  18. if strategy == BinsStrategyEnum.WIDTH.value:
  19. bin_width = (data[feat].max() - data[feat].min()) / nbins
  20. return pd.cut(data[feat], bins=nbins, labels=[f'Bin_{i}' for i in range(1, nbins + 1)])
  21. def f_get_woe(data: DataSplitEntity) -> pd.DataFrame:
  22. pass
  23. def f_get_iv(data: DataSplitEntity) -> pd.DataFrame:
  24. pass
  25. def f_get_psi(data: DataSplitEntity) -> pd.DataFrame:
  26. pass
  27. def f_get_corr(data: DataSplitEntity) -> pd.DataFrame:
  28. pass
  29. def f_get_ivf(data: DataSplitEntity) -> pd.DataFrame:
  30. pass