_partial.fit modifies estimator inplace

Questions from @mrocklin in https://github.com/dask/dask-ml/pull/275#issuecomment-402269422

> Shouldn't we be cloning the model here before calling partial fit? Otherwise we're mutating the input.
> What if we have to rerun this task because the worker that the result was on failed?

I'm not sure what happens when the worker fails :)

Let's say that

- Worker A completed `partial_fit` on the first block of data
- Worker B fails on the second block of data.

IIRC, when a worker fails during computation, the scheduler will mark the task as suspicions and reschedule the task on another worker. Let's say it's scheduled on worker C for whatever reason.

Worker C asks worker A for `fit--0`. I think everything is OK. The scheduler should always have a correct understanding of who has the latest successful fit call.

Does that sound right? Am I missing scenarios where we do something wrong?