On 29.04.2010 16:04, Eric Elguero wrote:
On Thu, 2010-04-29 at 15:08 +0200, Uwe Ligges wrote:
Well, it is called cross validation which is based on random sampling if
you do not have k=n -fold CV (=leave-one-out).
Again, to get reproducible results, you will need to set a seed.
thank you. I thought that "leave-one-out" was the default.
As you can see in ?stepclass:
fold parameter for cross-validation; omitted if ‘cv.groups’ is specified.
and the "Usage" line tells us:
..... fold = 10, ......
hence 10-fold is the default.
I looked at the reference file and I am not sure how to get it.
Is that by setting fold=1 ?
No, leave one out is n-fold, hence you need n!
Uwe Ligges
If the results are that unstable: Do you really have a sufficient number
of observations for your classification problem?
you're probably right.
e.e.
Eric Elguero
Laboratory Genetics and Evolution of Infectious Diseases,
Team: Genetics and Adaptation of Plasmodium
UMR 2724 CNRS-IRD,
IRD Montpellier,
911 Avenue Agropolis, BP 64501,
34394 Montpellier Cedex 5,
France
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