Yellowbrick v0.2

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.

Changes 

Intermediate steps towards a complete API for visualization. Preparatory stages for Scikit-Learn visual pipelines.

• Continued attempts to fix the Travis-CI Scipy install failure (broken tests)
• Utility function: get the name of the model
• Specified a class based API and the basic interface (render, draw, fit, predict, score)
• Added more documentation, converted to Sphinx, autodoc, docstrings for viz methods, and a quickstart
• How to contribute documentation, repo images etc.
• Prediction error plot for regressors (mvp)
• Residuals plot for regressors (mvp)
• Basic style settings a la seaborn
• ROC/AUC plot for classifiers (mvp)
• Best fit functions for "select best", linear, quadratic
• Several Jupyter notebooks for examples and demonstrations