Software Open Access

Yellowbrick v1.1

Bengfort, Benjamin; Bilbro, Rebecca; McIntyre, Kristen; Gray, Larry; Roman, Prema; Morris, Adam; Sharma, Shivendra; Chestnut, Michael; Garod, Michael; Bachwani, Naresh; Gautam, Piyush; Navarrete, Daniel; Morrison, Molly; Kwiecinska, Emma; Jain, Sarthak; Ojeda, Anthony; Schmierer, Edwin; Danielsen, Nathan

Yellowbrick is an open source, pure Python project that extends the scikit-learn API with visual analysis and diagnostic tools. The Yellowbrick API also wraps matplotlib to create publication-ready figures and interactive data explorations while still allowing developers fine-grain control of figures. For users, Yellowbrick can help evaluate the performance, stability, and predictive value of machine learning models and assist in diagnosing problems throughout the machine learning workflow.

Major Changes:

  • Quick methods (aka Oneliners), which return a fully fitted finalized visualizer object in only a single line, are now implemented for all Yellowbrick Visualizers. Test coverage has been added for all quick methods. The documentation has been updated to document and demonstrate the usage of the quick methods.

  • Added Part of Speech tagging for raw text using spaCy and NLTK to POSTagVisualizer.

Minor Changes:

  • Adds Board of Directors minutes for Spring meeting.

  • Miscellaneous documentation corrections and fixes.

  • Miscellaneous CI and testing corrections and fixes.

Files (59.4 MB)
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