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A problem with Elastic net + Cox regression

I was trying to perform elastic net + cox regression in R using the glmnet package. The problem is that my data is around 100 individuals with ~100k features and the model is too big for R to store in a matrix. Although the glmnet package can use sparse matrix for the model unfortunately it does not support it with Cox regression.

Anyone knows of another tool I can use (I am not locked in R, it was just the only tool I found)? I read that I can use an SVM (support vector machine) but I still need to calculate the model. I am looking for any tool (R, Matlab, stand alone application) that can perform elastic net + cox regression on a big model. Furthermore, maybe you know how to calculate this big model as a stand alone output so I can use it in an SVM?

cox r

1 answer

I fixed the issue. My model was becoming too big because of how I did my test case. If I use the example at https://cran.r-project.org/web/packages/glmnet/glmnet.pdf it works perfectly.

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