Yellowbrick v1.1
Benjamin Bengfort, Rebecca Bilbro, Kristen McIntyre, Larry Gray, Prema Roman, Adam Morris, Shivendra Sharma, Michael Chestnut, Michael Garod, Naresh Bachwani, Gautam, Piyush, Daniel Navarrete, Morrison, Molly, Emma Kwiecinska, Jain, Sarthak, Anthony Ojeda, Edwin Schmierer, Nathan Danielsen · Zenodo (CERN European Organization for Nuclear Research) · 2020
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.