I m getting a weird error when training a glmnet regression.
invalid class "dgCMatrix" object: length(Dimnames[[2]]) must match Dim[2]
It only happens occasionally, and perhaps only under larger datasets.
I m not sure whether it s consistent it happens given a certain dataset.
Any clues?
Without knowing the particulars of this packages, John Chambers "Software for Data Analsys" (2008, Springer) has a good discussion on debugging, for example via
> options(error=recover)
which may be of help here.
I kept getting the same error while using family= binomial . Turns out I had too few events/cases in my response variable. Using nfold=10 in cv.glmnet, I would get the error if my binary response [0,1] occured less than ~2% of the time. I recommend having your script check for this scenario and use glmnet when true. You won t get the benefit of the x validation for selecting lambda though.
Need to clarify the above. I had this problem when using cv.glmnet(). By identifying those instances where there are too few cases, I used glmnet() instead. You lose the benefit of the cross validation (i.e. estimating lambda), but it will complile.
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