R-based objective function for L1- or L2-regularized logistic regression

R-based objective function for L1- or L2-regularized logistic regression

objective_r(beta0, beta, x, y, lambda, alpha = 0)

Arguments

beta0

intercept
beta

a feature matrix
x

observations
y

response
lambda

penalty
alpha

elasticnet mixing parameter

Value

Objective function value.

Examples

if (requireNamespace("glmnet")) {
  x <- matrix(rnorm(100*20), 100, 20)
  y <- sample(1:2, 100, replace = TRUE)
  fit <- glmnet::cv.glmnet(x, y, family = "binomial")
  lambda <- fit$lambda.1se
  beta0 <- coef(fit, lambda)[1]
  beta <- coef(fit, lambda)[-1]
  objective_r(beta0, beta, t(x), y, lambda, alpha = 1)
}
#> [1] 0.6529418