matlab - Gaussian Processes for Regression (GPR) and Logistic Regression (LR) -

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i want implement model risk prediction (generate percentage). know lr adequate work try gpr.

my question is: gpr suitable choice in case? know gpr generate probability distribution on function , can give robust estimation missing data possible make probabilistic prediction? (or gaussian processes classification can this?)

thank help. :-)

gpr regression problem. lr "classification".

you should use gaussian process followed nonlinearity (like softmax) classification needs approximations learning , prediction. included in following link. can run demo see how works: http://www.gaussianprocess.org/gpml/code/matlab/doc/


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