On 7 January 2017 at 21:20, Sebastian Raschka <se.rasc...@gmail.com> wrote:
> Hi, Thomas, > sorry, I overread the regression part … > This would be a bit trickier, I am not sure what a good strategy for > averaging regression outputs would be. However, if you just want to compute > the average, you could do sth like > np.mean(np.asarray([r.predict(X) for r in list_or_your_mlps])) > > However, it may be better to use stacking, and use the output of > r.predict(X) as meta features to train a model based on these? > Like to train an SVR to combine the predictions of the top 10% MLPRegressors using the same data that were used for training of the MLPRegressors? Wouldn't that lead to overfitting? > > Best, > Sebastian > > > On Jan 7, 2017, at 1:49 PM, Thomas Evangelidis <teva...@gmail.com> > wrote: > > > > 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 > > _______________________________________________ > > 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 > -- ====================================================================== 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/
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