SciKit Learn: Multilayer perceptron early stopping, restore best weights
To restore the best weights you would need a way to monitor a metric of your choosing and keep track of the best weights up to a given point. This has nothing to do with early stopping, you could return the best weights regardless of how many iterations the classifier has performed. Unfortunately, as far as I know, this functionality is not supported by scikit-learn. 

In early stopping you assume that the best weights are those that the point you stopped your training. Early stopping isn't as much a convergence speed technique as it is a regularization, one.