The problem was that I had a loop like
for i in xrange(len(clf.feature_importances_)):
print clf.feature_importances_[i]
which recomputes the feature importance array in every step.
Obvious in hindsight.
Raphael
On 21 July 2016 at 16:22, Raphael C wrote:
> I have a set of feature vectors
I have a set of feature vectors associated with binary class labels,
each of which has about 40,000 features. I can train a random forest
classifier in sklearn which works well. I would however like to see
the most important features.
I tried simply printing out forest.feature_importances_ but thi
