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$
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. 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
