Comments (6)
What is wrong with your current code?
(expect that you might want to specify a common cv.ind
)
from biglasso.
Hi @privefl,
Thanks for the answer. I don't think the alpha value is defined in the cv.biglasso function, and the default is l1-penalization (alpha = 1). Can you correct me if I'm wrong?
from biglasso.
From the documentation, you can see ... Additional arguments to biglasso.
So, you can use alpha
in cv.biglasso
too.
from biglasso.
Sample data
X <- replicate(30,rnorm(100))
Y <- sample(c(0,1), replace=TRUE, size=100)
Bigmatrix
X.bm <- as.big.matrix(X)
CV
cv <- cv.biglasso(X.bm, Y, family = "binomial", nfolds = 5, ncores = 3, seed = 123, alpha = 1)
Summary
summary(cv)
Repeating the code with alpha = 0 gives me the same result. How can the alpha value be assigned?
from biglasso.
You need to also add penalty = "ridge"
.
from biglasso.
Ah of course! Glmnet asks only for alpha, so did not think of this. Thanks a lot @privefl ! I'll close the "issue".
from biglasso.
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