Clarification Request On Problem 13
 

If a data set is not separable using RBF in the Z-space then the QP solver will hit the iteration limit and bomb. If the solver completes and returns an alpha vector that happens to provide zero in-sample error with the test data set then how does that indicate that the training data was not linearly separable? Is every occurrence of zero in-sample error during testing to be interpreted as a failure to separate the training data? I don't understand the operating procedure specified by the problem text.

Thanks for your attention.

Re: Clarification Request On Problem 14
 

If you get 's that achieve zero in-sample error, then the training data is separable by definition (those separating 's are an existence proof of that fact).

Re: Clarification Request On Problem 14
 

Thanks for the prompt response.

Ein of zero is perfectly separated. I understand that. Perhaps my confusion arose from thinking about the PLA and how it can fail spectacularly when confronted with non-separable data. I had the impression that missing a few target function points during the in-sample error calculation wasn't a problem of the same magnitude as the solver being unable to converge to any solution at all.

I will talley up the Ein=0 statistics as specified in the problem instructions. Thanks.