xRiskLab/fastwoe
Fast Weight of Evidence (WOE) Encoding and Inference
This tool helps data analysts and machine learning practitioners prepare categorical and numerical data for predictive models, especially in areas like credit scoring or risk assessment. You feed in raw data with categories (like 'customer segment' or 'city') and a target outcome (like 'loan default' or 'fraud'), and it outputs transformed data where categories are replaced by statistical scores that better predict the target. This transformation makes your models more accurate and easier to interpret.
Available on PyPI.
Use this if you need to transform categorical and numerical features into statistically meaningful scores (Weight of Evidence) to improve the performance and interpretability of your machine learning models, particularly for classification problems with binary or multiple outcomes.
Not ideal if your primary goal is deep learning, unsupervised learning, or if you don't need interpretable feature transformations for classification tasks.
Stars
20
Forks
3
Language
Python
License
MIT
Category
Last pushed
Jan 11, 2026
Commits (30d)
0
Dependencies
8
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