[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
Yes, that makes sense. It was not intended that the take-home message is "GPs are better than ensembles", even though its sounds a bit like that admittedly. The target function matches very nicely to the assumptions of the squared-exponential kernel, which surely helps the GP. I will adapt this once I find time