On 10 September 2017 at 22:03, Sebastian Raschka <se.rasc...@gmail.com> wrote:
> You could normalize the outputs (e.g., via min-max scaling). However, I > think the more intuitive way would be to clip the predictions. E.g., say > you are predicting house prices, it probably makes no sense to have a > negative prediction, so you would clip the output at some value >0$ > > By clipping you mean discarding the predictors that give values below/above the threshold? > PS: -820 and -800 sounds a bit extreme if your training data is in a -5 to > -9 range. Is your training data from a different population then the one > you use for testing/making predictions? Or maybe it's just an extreme case > of overfitting. > > It is from the same population, but the training sets I use are very small (6-32 observations), so it must be over-fitting. We had that discussion in the past here, yet in practice I get good correlations with the experimental values using MLPRegressors. > Best, > Sebastian > > > > On Sep 10, 2017, at 3:13 PM, Thomas Evangelidis <teva...@gmail.com> > wrote: > > > > Greetings, > > > > Is there any way to force the MLPRegressor to make predictions in the > same value range as the training data? For example, if the training data > range between -5 and -9, I don't want the predictions to range between -820 > and -800. In fact, some times I get anti-correlated predictions, for > example between 800 and 820 and I have to change the sign in order to > calculate correlations with experimental values. Is there a way to control > the value range explicitly or implicitly (by post-processing the > predictions)? > > > > thanks > > Thomas > > > > > > -- > > ====================================================================== > > Dr Thomas Evangelidis > > Post-doctoral Researcher > > CEITEC - Central European Institute of Technology > > Masaryk University > > Kamenice 5/A35/2S049, > > 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 > -- ====================================================================== Dr Thomas Evangelidis Post-doctoral Researcher CEITEC - Central European Institute of Technology Masaryk University Kamenice 5/A35/2S049, 62500 Brno, Czech Republic email: tev...@pharm.uoa.gr teva...@gmail.com website: https://sites.google.com/site/thomasevangelidishomepage/
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