Yellowbrick v0.1

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. Changelog Created the Yellowbrick library MVP with two primary operations: a classification report heat map and a ROC/AUC curve model analysis for classifiers. This is the base package deployment for continuing Yellowbrick development. Created the anscombe quartet visualization example Added DDL specific color maps and a stub for more style handling Created crplot which visualizes the confusion matrix of a classifier Created rocplot_compare which compares two classifiers using ROC/AUC metrics Stub tests/stub documentatio