[scikit-learn] meta-estimator for multiple MLPRegressor

[Thomas Evangelidis]

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.raschka at 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 <tevang3 at 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: tevang at pharm.uoa.gr
> >               tevang3 at gmail.com
> >
> > website: https://sites.google.com/site/thomasevangelidishomepage/
> >
> >
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