Use float as percentage in min_samples_split and min_samples_leaf of DecisionTree

A float number can be used as percentage in these two parameters in case the sample size varies greatly.

I found a new parameter `min_weight_fraction_leaf` is added recently. It works in a similar way. But it is still convenient to use float in `min_samples_split` for those sample without weighting.
this, together with your validation below, will let through floats >1, which makes no sense. Why not just use `0 < self.min_samples_leaf < 1`?