Changes

Added examples on how to extend Auto-sklearn with a custom classifier, regressor, and preprocessor.
Auto-sklearn now requires numpy version between 1.9.0 and 1.14.5, due to higher versions causing travis failure.
Examples now use sklearn.datasets.load_breast_cancer() instead of sklearn.datasets.load_digits() to reduce memory usage for travis build.
Fixes future warnings on non-tuple sequence for indexing.
Fixes #500: fixes ensemble builder to correctly evaluate model score with any metrics. See PR #522.
Fixes #482 and #491: Users can now set up custom logger configuration by passing a dictionary created by a yaml file to logging_config.
Fixes #566: ensembles are now sorted correctly.
Fixes #293: Auto-sklearn checks if appropriate target type was given for classification and regression before call to fit().
Travis-ci now runs flake8 to enforce pep8 style guide, and uses travis-ci instead of circle-ci for deployment.

Contributors