Yes, exactly.
Le 12 sept. 2014 18:31, "Luca Puggini" a écrit :
> Hey thanks a lot,
> so basically in random Forest the split is done like in the algorithm
> described in your thesis except that the search is not done on all the
> variables but only on a random subset of them? (usually sqrt(p) or
Hey thanks a lot,
so basically in random Forest the split is done like in the algorithm
described in your thesis except that the search is not done on all the
variables but only on a random subset of them? (usually sqrt(p) or
something like that)
Let me know.
Thanks,
Luca
Hi Luca,
>
> The "best"
Hi Luca,
The "best" strategy consists in finding the best threshold, that is the one
that maximizes impurity decrease, when trying to partition a node into a
left and right nodes. By contrast, "random" does not look for the best
split and simply draw the discretization threshold at random.
For fu
Hi,
I am using random forest classifier and this algorithm train a tree defined
as :
DecisionTreeClassifier(criterion='gini', max_depth=None,
max_features='auto',
max_leaf_nodes=None, min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, random_state=198200
