adc-trust-ai/trust-free
An interpretable regression model in Python with Random-Forest-level accuracy
This tool helps data analysts and scientists create predictive models that are both highly accurate and easy to understand. It takes in tabular data and outputs a regression model that can forecast outcomes, along with clear, natural-language explanations of how each prediction is made. This is ideal for professionals in fields where model transparency and auditability are crucial.
Available on PyPI.
Use this if you need to build robust regression models that deliver Random Forest-level accuracy while also providing complete transparency and interpretable explanations for every prediction.
Not ideal if you are working with datasets larger than 5,000 rows or 20 columns and require full functionality beyond the included standalone utilities.
Stars
11
Forks
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Language
Jupyter Notebook
License
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Last pushed
Mar 09, 2026
Commits (30d)
0
Dependencies
13
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