>
> That said, as Olivier mentioned, the GradientBoostingClassifier could
>> implement a "transform", and that might be a good idea.
>>
>
> Ok, then maybe that's something I can tackle if it's not to hairy ?
>
>
I tried something really dumb, but it seems to work in my case:
"""
class ExtGradientBoostingClassifier(GradientBoostingClassifier,
_LearntSelectorMixin):
pass
clf = ExtGradientBoostingClassifier()
clf.fit(X,y)
X = clf.transform(X)
X_valid = clf.transform(X_valid)
clf = GradientBoostingClassifier(n_estimators=100, max_depth=10)
clf.fit(X,y)
y_pred = clf.predict(X_valid)
...
"""
So I created a PR for this :
https://github.com/scikit-learn/scikit-learn/pull/2167
It seems that s.o. already added the pointer to the scipy tutorials though
:)
E/
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