A cross validation hyper-parameter optimization module.
This module uses Bayesian optimization and Gaussian Processes to find optmum set of cross validation parameters. It uses the cross_val_score and Gaussian Processes objects from sklearn.
Ultimately the goal is to add this technique to sklearn's cross validation / model selection module.