Greetings, I want to train a MLPClassifier with one hidden layer and use it as a feature selector for an MLPRegressor. Is it possible to get the values of the neurons from the last hidden layer of the MLPClassifier to pass them as input to the MLPRegressor?
If it is not possible with scikit-learn, is anyone aware of any scikit-compatible NN library that offers this functionality? For example this one: http://scikit-neuralnetwork.readthedocs.io/en/latest/index.html I wouldn't like to do this in Tensorflow because the MLP there is much slower than scikit-learn's implementation. 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