scikit-learn-contrib
Using existing numpy RandomState
The _get_random_state implementation in base.py forces all estimators to only take integer seed values for the random_state attribute. I'd like the functionality to pass an existing RandomState object. This is useful when using lightning objects as part of other estimators.
Unfortunately I'm not sure if this is compatible with the randomkit backport here.
Can we set the internal state of lightning's random state from numpy's?
BTW, oiriginally I added the randomkit backport so that we can use randint in tight loops. However, this can also be achieved by generating a random array before the loop. So, with a bit of work, we could possibly remove the randomkit if necessary.
