owlqn_r: OWL-QN for optimising loss_smooth R implementation

In edahelsinki/slise: Sparse Linear Subset Explanations

OWL-QN for optimising loss_smooth R implementation

Description

OWL-QN for optimising loss_smooth R implementation

Usage

owlqn_r(
  alpha,
  X,
  Y,
  epsilon,
  beta,
  lambda1 = 0,
  lambda2 = 0,
  weight = NULL,
  max_iterations = 300,
  ...,
  invisible = TRUE
)

Arguments

alpha	linear model to optimise
X	data matrix
Y	response vector
epsilon	error tolerance
beta	sigmoid steepness
lambda1	L1 coefficient (default: 0)
lambda2	L1 coefficient(default: 0)
weight	weight vector (default: NULL)
max_iterations	number of OWL-QN iterations (default: 300)
...	other parameters to OWL-QN
invisible	no terminal output (default: TRUE)

Value

lbfgs object

edahelsinki/slise documentation built on Aug. 24, 2023, 11:03 p.m.