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 <[email protected]> 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: [email protected] > [email protected] > > website: https://sites.google.com/site/thomasevangelidishomepage/ > > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list [email protected] https://mail.python.org/mailman/listinfo/scikit-learn
