Greetings,
I don't know if anyone encountered this before, but sometimes I get
anti-correlated predictions by the SVR I that am training. Namely, the
Pearson's R and Kendall's tau are negative when I compare the predictions
on the external test set with the true values. However, the SVR predictions
on the training set have positive correlations with the experimental values
and hence I can't think of a way to know in advance if the trained SVR will
produce anti-correlated predictions in order to change their sign and avoid
the disaster. Here is an example of what I mean:
Training set predictions: R=0.452422, tau=0.333333
External test set predictions: R=-0.537420, tau-0.300000
Obviously, in a real case scenario where I wouldn't have the external test
set I would have used the worst observation instead of the best ones. Has
anybody any idea about how I could prevent this?
thanks in advance
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/
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