[MRG] Prediction variance in bagging-based regressors

This addresses issue  #3271. The main points are
 * Option with_std added to method predict of BaggingRegressor and RandomForestRegressor. If True, the standard deviation of the predictions is returned in addition to the mean
 * Added option with_std to GaussianProcess.predict() and deprecated eval_MSE, which returned the predictive variance
 * Added one example comparing the predictive distributions of the three methods.

Please also check the planned deprecation path of the parameter eval_MSE in GaussianProcess
It's hard to tell which method has better variance estimates without an objective metric. So I would rather remove this sentence. I would add in the example description that GP models the predictive distribution in a Bayesian way, while RF and Bagging use frequentist variance estimates and that no parametric assumption are made on the predictive distribution.