Hi Bruno,
You advised following
no need to find the best s value. CV does it for you:
cvres<-cv.lars(X,Y,K=10,type='lasso')
sAtBest<-cvres$fraction[which.min(cvres$cv)]
fits <- predict.lars(object, type="coefficients", s=sAtBest,
mode="fraction")
in thread https://stat.ethz.ch/pipermail/r-help/2007-June/133982.html
My problem is that, cvres$cv is non empty but cvres$fraction is null so I am
unable to fetch sAtBest.
What am I doing wrong here?
Thanks in anticipation.
Regards,
Bhuvneshwar
Algorithm Engineer
Adobe
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