I tried the sklearn.neural_network.MLPClassifier with the default
parameters using the input data I quoted in my previous post about
Nu-Support Vector Classifier. The predictions are great but the problem is
that sometimes when I rerun the MLPClassifier it predicts no positive
observations (class 1). I have noticed that this can be controlled by the
random_state parameter, e.g. MLPClassifier(random_state=0) gives always no
positive predictions. My question is how can I chose the right random_state
value in a real blind test case?
thanks in advance
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/
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