DistrictDataLabs/yellowbrick
A suite of visual diagnostic tools extending scikit-learn to facilitate machine learning model selection.
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Yellowbrick provides visual analysis and diagnostic tools designed to help data scientists steer the model selection process. It extends the scikit-learn API with matplotlib-based visualizers that display metrics like confusion matrices, ROC curves, and feature importances. The library integrates directly into scikit-learn workflows, offering estimators for classification, regression, and clustering visualization.
Frequently asked
- What is DistrictDataLabs/yellowbrick?
- A suite of visual diagnostic tools extending scikit-learn to facilitate machine learning model selection.
- Is yellowbrick open source?
- Yes — DistrictDataLabs/yellowbrick is open source, released under the Apache-2.0 license.
- What language is yellowbrick written in?
- DistrictDataLabs/yellowbrick is primarily written in Python.
- How popular is yellowbrick?
- DistrictDataLabs/yellowbrick has 4.4k stars on GitHub.
- Where can I find yellowbrick?
- DistrictDataLabs/yellowbrick is on GitHub at https://github.com/DistrictDataLabs/yellowbrick.