Hi Sebastian, Thanks, I will try it in another classification problem I have. However, this time I am using regressors not classifiers.
On Jan 7, 2017 19:28, "Sebastian Raschka" <se.rasc...@gmail.com> wrote: > Hi, Thomas, > > the VotingClassifier can combine different models per majority voting > amongst their predictions. Unfortunately, it refits the classifiers though > (after cloning them). I think we implemented it this way to make it > compatible to GridSearch and so forth. However, I have a version of the > estimator that you can initialize with “refit=False” to avoid refitting if > it helps. http://rasbt.github.io/mlxtend/user_guide/classifier/ > EnsembleVoteClassifier/#example-5-using-pre-fitted-classifiers > > Best, > Sebastian > > > > > On Jan 7, 2017, at 11:15 AM, Thomas Evangelidis <teva...@gmail.com> > wrote: > > > > Greetings, > > > > I have trained many MLPRegressors using different random_state value and > estimated the R^2 using cross-validation. Now I want to combine the top 10% > of them in how to get more accurate predictions. Is there a meta-estimator > that can get as input a few precomputed MLPRegressors and give consensus > predictions? Can the BaggingRegressor do this job using MLPRegressors as > input? > > > > Thanks in advance for any hint. > > Thomas > > > > > > -- > > ====================================================================== > > Thomas Evangelidis > > Research Specialist > > CEITEC - Central European Institute of Technology > > Masaryk University > > Kamenice 5/A35/1S081, > > 62500 Brno, Czech Republic > > > > email: tev...@pharm.uoa.gr > > teva...@gmail.com > > > > website: https://sites.google.com/site/thomasevangelidishomepage/ > > > > > > _______________________________________________ > > scikit-learn mailing list > > scikit-learn@python.org > > https://mail.python.org/mailman/listinfo/scikit-learn > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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