I tried the following glmnet code and got differnt coefficient results. In the glmnet, doesn't "binomial" basically mean logit?? I wonder why the results are different.
clf<-cv.glmnet(X_train, fa_train, family=binomial, alpha=1, nlambda=100, standardize=TRUE, type.measure="auc")
clf2<-cv.glmnet(X_train, fa_train, family=binomial(link="logit"), alpha=1, nlambda=100, standardize=TRUE, type.measure="auc")