Hello all,
I want to optimize n_estimators and max_features for ensemble methods (say
forRandomForestClassifier ).
Usually I use GridSearchCV() with cv=4 which do 4 fold cross validation for
data and gives best parameter/model.
In the document section 'out-of-bag-estimates'
http://scikit-learn.org/dev/modules/grid_search.html#out-of-bag-estimates
says 'left out portion can be used to estimate the generalization error
without having to rely on a separate validation set'.
'out-of-bag-estimates' suggests GridSearchCV() is not needed in this
case!!
If so how do I get best parameter values and model.
Or I got the whole concept wrong?
Thanks.
--
Sheila
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