I have an x-matrix of 8 columns. I want to run glmnet to do a lasso regression. I know I need to call:
glmnet(x, y, family = "binomial", ...).
However, how do I get x to consider all one way interactions as well? Do I have to manually remake the dataframe and if so is there an easier way? I suppose I was hoping to do something of an R formula.
Yes, there is a convenient way for that. Two steps in it are important.
library(glmnet) # Sample data data <- data.frame(matrix(rnorm(9 * 10), ncol = 9)) names(data) <- c(paste0("x", 1:8), "y") # First step: using .*. for all interactions f <- as.formula(y ~ .*.) y <- data$y # Second step: using model.matrix to take advantage of f x <- model.matrix(f, data)[, -1] glmnet(x, y)