Visual analysis and diagnostic tools to facilitate machine learning model selection
Yellowbrick
Visual analysis and diagnostic tools to facilitate machine learning model selection.
What is Yellowbrick?
Yellowbrick is a suite of visual diagnostic tools called “Visualizers” that extend the scikit-learn API to allow human steering of the model selection process. In a nutshell, Yellowbrick combines scikit-learn with matplotlib in the best tradition of the scikit-learn documentation, but to produce visualizations for your machine learning workflow!
For complete documentation on the Yellowbrick API, a gallery of available visualizers, the contributor’s guide, tutorials and teaching resources, frequently asked questions, and more, please visit our documentation at www.scikit-yb.org.
Installing Yellowbrick
Yellowbrick is compatible with Python 3.4 or later and also depends on scikit-learn and matplotlib. The simplest way to install Yellowbrick and its dependencies is from PyPI with pip, Python’s