objective_r: R-based objective function for L1- or L2-regularized logistic...
In jolars/gsoc18saga: Test results for SAGA project in GSoC 2018

Description Usage Arguments Value Examples

View source: R/objective.R

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

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

`beta0`	intercept
`beta`	a feature matrix
`x`	observations
`y`	response
`lambda`	penalty
`alpha`	elasticnet mixing parameter

Objective function value.

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)
}