def Predictor.woe_encode(self, data=None, subset=None) [source]
Apply trained WOE encoding to input data.
Converts binned features into Weight of Evidence values
using the bin-level target rates locked during training.
Parameters
data : pDF | None
Input data (binned features). If None, returns the
trained WOE encoding map.
trained WOE encoding map.
subset : list
Specific features to process and return (including IXN).
Default = None: all trained features.
Default = None: all trained features.
Returns
WoeEncoderResult | dict
• data provided: data of WOE-encoded features
• data is None: trained WOE values per bin
• data is None: trained WOE values per bin