[WIP] Bagging ensemble meta-estimator

Hi,

This is a very early PR for a meta-estimator ensemble implementing ensemble averaging/voting. The idea is to make a meta-estimator that can take as input any type of base estimator (not only trees) and make an ensemble out of it. This should work quite well for estimators with high variance (trees, gbrt, neural networks typically).

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TODO list:

- [x] rename to `BaggingClassifier` and `BaggingRegressor`.
- [x] add `subsampling` hyper-parameter.
- [x] add `subsampling_features` hyper-parameter.
- [ ] documentation
- [x] tests
- [ ] examples