Intermediate steps towards a complete API for visualization. Preparatory stages for Scikit-Learn visual pipelines.
Deployed: Sunday, September 4, 2016
Contributors: Benjamin Bengfort, Rebecca Bilbro, Patrick O'Melveny, Ellen Lowy, Laura Lorenz
- 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