Hello,
Thanks for the excellent package. The functions are super helpful, and they make life much simpler while fitting glmnet models on a given dataset. One additional feature that I think would be great to have is an option of returning the predictor (and response) matrices created from the formula while fitting the model. This will be similar to the lm() and glm() functions where the logical arguments x and y determine whether these matrices/vectors are to be returned with the output. This is particularly useful e.g., in a post-analysis where one fits another model (say, a random forest) with the same predictors used in the glmnet.
Thanks,
Saptarshi
Hello,
Thanks for the excellent package. The functions are super helpful, and they make life much simpler while fitting
glmnetmodels on a given dataset. One additional feature that I think would be great to have is an option of returning the predictor (and response) matrices created from the formula while fitting the model. This will be similar to thelm()andglm()functions where the logical argumentsxandydetermine whether these matrices/vectors are to be returned with the output. This is particularly useful e.g., in a post-analysis where one fits another model (say, a random forest) with the same predictors used in theglmnet.Thanks,
Saptarshi