My first question is what kind of a problem generates >5000 Xs
on each of 15 observations? David
James T Metz wrote:
>
> JMP Users,
>
> I have a general question concerning model validation. Does
> anyone have any thoughts or comments concerning
> (Y data) (multiple) scrambling (using the column shuffle option in
> JMP) versus hold-out data sets (using excluded rows) as
> a means to "validate" models? Is one method generally preferred over
> the other? Is one method generally better for regression
> while another method is better for partition models, etc? Is the
> number of observations important?
>
> Case-in-point - I have a data set of about 15 observables (Y
> values). I can obtain > 5000 X values (descriptors or columns)
> for each of the rows. Obviously, there is a great, and highly likely
> danger of chance correlation. I could use either method mentioned
> above to "validate" generated models. However, my intuition says that
> the hold-out method is not appropriate in this case, since my
> data set is so small. Do others agree?
>
> I welcome thoughts, comments, literature references, etc.
>
> Regards,
> Jim Metz
>
> James T. Metz, Ph.D.
> Research Investigator Chemist
>
> GPRD R46Y AP10-2
> Abbott Laboratories
> 100 Abbott Park Road
> Abbott Park, IL 60064-6100
> U.S.A.
>
> Office (847) 936 - 0441
> FAX (847) 935 - 0548
>
> james.metz@abbott.com
>
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