I didn’t realize that. I thought it was the name of the class.
Thank you,
From: Eraldo Pomponi [mailto:[email protected]]
Sent: Tuesday, September 23, 2014 4:56 PM
To: [email protected]
Subject: Re: [Scikit-learn-general] name of random forest classifier params in
pipeline
Dear Roberto,
On Wed, Sep 24, 2014 at 12:14 AM, Pagliari, Roberto
<[email protected]<mailto:[email protected]>> wrote:
I’m using a pipeline with gridsearchcv. I tried this to allow search over a
range of number of trees
params = dict(random_forest_classifier__n_estimators=[8, 9, 10, 11])
clf = grid_search.GridSearchCV(my_pipeline, param_grid=params)
but the name ‘random_forest_classifier__n_estimators’ is not correct. What is
the name for it, and how do I find these names for different classifiers?
You must use the name that you (arbitrary) assigned to this estimator in the
Pipeline:
my_pipeline = Pipeline([
('randomf', RandomForestClassifier())
])
params_grid = {
'randomf__n_estimators': [30, 50, 100],
}
clf = GridSearchCV(my_pipeline, params_grid)
HTH,
Eraldo
------------------------------------------------------------------------------
Meet PCI DSS 3.0 Compliance Requirements with EventLog Analyzer
Achieve PCI DSS 3.0 Compliant Status with Out-of-the-box PCI DSS Reports
Are you Audit-Ready for PCI DSS 3.0 Compliance? Download White paper
Comply to PCI DSS 3.0 Requirement 10 and 11.5 with EventLog Analyzer
http://pubads.g.doubleclick.net/gampad/clk?id=154622311&iu=/4140/ostg.clktrk
_______________________________________________
Scikit-learn-general mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
