slise_initialisation_ols: Initialise the graduated optimisation with an "Ordinary Least...

In edahelsinki/slise: Sparse Linear Subset Explanations

Initialise the graduated optimisation with an "Ordinary Least Squares" solution

Description

Initialise the graduated optimisation with an "Ordinary Least Squares" solution

Usage

slise_initialisation_ols(
  X,
  Y,
  epsilon,
  weight = NULL,
  beta_max = 20/epsilon^2,
  max_approx = 1.15,
  max_iterations = 300,
  beta_max_init = 2.5/epsilon^2,
  ...
)

Arguments

X	data matrix
Y	response vector
epsilon	error tolerance
weight	weight vector (default: NULL)
beta_max	the maximum starting sigmoid steepness (default: 20/epsilon^2)
max_approx	the target approximation ratio (default: 1.15)
max_iterations	if ncol(X) is huge, then ols is replaced with optimisation (default:300)
beta_max_init	the maximum sigmoid steepness in the initialisation
...	unused parameters

Value

list(alpha, beta)

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