Linear regression — linear_regression • baritsu

A wrapper around mlpack::linear_regression() and mlpack::lars() that allows passing a formula.

Usage

linear_regression(
  formula = NULL,
  data = NULL,
  lambda1 = 0,
  lambda2 = 0,
  no_intercept = FALSE,
  no_normalize = FALSE,
  use_cholesky = FALSE,
  x = NULL,
  y = NULL
)

Arguments

formula: A formula.
data: A data.frame.
lambda1: Regularization parameter for L1-norm penalty.
lambda2: Regularization parameter for L2-norm penalty.
no_intercept: Logical; passed to mlpack::lars().
no_normalize: Logical; passed to mlpack::lars().
use_cholesky: Logical; passed to mlpack::lars().
x: Design matrix.
y: Response matrix.

Value

An object of class baritsu_lr.

Details

When the lambda1 is 0, this function fallbacks to mlpack::linear_regression() for performance.

See also

mlpack::linear_regression() mlpack::lars() predict.baritsu_lr()