Add cross_validate helper

`sklearn.model_selection.cross_validate` fits and scores several models over some CV splits of data.

http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_validate.html

Users can currently do this distributed on a cluster with

```python
import dask_ml.joblib

with joblib.parallel_backend('dask', scatter=[X, y]):
sklearn.model_selection.cross_validate(estimator, X, y)
```

Why not do that for them by defining a `dask_ml.model_selection.cross_validate` that does the `parallel_backend` and `scatter`ing for them?