`seed` same in different objects about rforestry

[edwardwliu]

It sounds like two RandomForest objects will have different seeds when instantiated, but the objects are considered equal since the default value of seed=randrange() is the same. Is this still an issue if we the class explicitly assigns the seed in an initialization or post initialization step (even when the user doesn't provide one)?

[petrovicboban]

Two RandomForest objects will have the same seeds when instantiated. Although, it you re-run script, seed value will be different, but again, the same for both objects.
I don't think we can do it in __init__ and still pass all tests in test_sklearn_compatible_estimator.
The only way to do it is to do it at the start of fit like we do for some other parameters: leave the parameter in __init__ but set default value to None, and then, in fit, check if it's None, and set random value if it is.

[petrovicboban]

Actually, we can't do it. We'll have to move seed to fit parameters.