Getting glmnet coefficients at 'best' lambda

Question

I am using following code with glmnet:

> library(glmnet)
> fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1])
> plot(fit, xvar=\'lambda\')

Answer 1

Try this:

fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1], 
    lambda=cv.glmnet(as.matrix(mtcars[-1]), mtcars[,1])$lambda.1se)
coef(fit)

Or you can specify a specify a lambda value in coef:

fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1])
coef(fit, s = cv.glmnet(as.matrix(mtcars[-1]), mtcars[,1])$lambda.1se)

You need to pick a "best" lambda, and lambda.1se is a reasonable, or justifiable, one to pick. But you could use cv.glmnet(as.matrix(mtcars[-1]), mtcars[,1])$lambda.min or any other value of lambda that you settle upon as "best" for you.