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logpost
2007 Mar 15
1
Model selection in LASSO (cross-validation)
...hat we can also use cross validation as a criterion too. I used
cv.lars to give me the lowest predicted error & fraction. But I'm short of
a step to arrive at the number of variables to be included in the final
model. How do we do that? Is it the predict.lars function? i tried >
logprostate.plars.cv=predict.lars(logprostate.lars.cv, M, type = "fit",
mode="fraction") but it gives me error message:
Error in dim(data) <- dim : attempt to set an attribute on NULL. Please
help!
thanks!
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