Comments (4)
Hi. Thank you for reporting. I think we've got an issue here. How do you call KPLS()
, what options are you using? What is the dimension of your training inputs and the value of n_comp
?
In 2.4, we've changed the default internal optimizer from COBYLA to TNC. The latter uses gradients, I guess that if you switch back to COBYLA by using KPLS(hyper_opt="Cobyla", ...)
you will retrieve a working solution.
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-
the point of using
KPLS
orKPLSK
is to choosen_comp < num_params
to get actual dimension reduction otherwise you'd better useKRG
. What is the value ofnum_params
? Whats is the shape of your training data (n_samples, n_dim) ? What is the shape/value oft0s
? -
what version of SMT worked for you before?
-
did you try to increase the nugget like it was suggested (option
nugget=1e-8
) when you test with Cobyla? -
If you go back to
TNC
you get an error, correct? At the moment I can not reproduce the error you've got. So without an actual example to reproduce the error, it is difficult to help you more on this.
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