interpretml/DiCE
DiCE generates diverse counterfactual explanations to explain any machine learning model's predictions.
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DiCE (Diverse Counterfactual Explanations) is an explainable AI library that generates multiple possible counterfactuals showing how inputs could change to achieve different outcomes. It works with any machine learning model including sklearn, TensorFlow, and PyTorch. The tool helps users understand model behavior by presenting actionable, interpretable alternatives to specific predictions.
Frequently asked
- What is interpretml/DiCE?
- DiCE generates diverse counterfactual explanations to explain any machine learning model's predictions.
- Is DiCE open source?
- Yes — interpretml/DiCE is open source, released under the MIT license.
- What language is DiCE written in?
- interpretml/DiCE is primarily written in Python.
- How popular is DiCE?
- interpretml/DiCE has 1.5k stars on GitHub.
- Where can I find DiCE?
- interpretml/DiCE is on GitHub at https://github.com/interpretml/DiCE.