set.control.newton: Check and set the control parameters for the Newton algorithm

In sgdGMF: Estimation of Generalized Matrix Factorization Models via Stochastic Gradient Descent

Check and set the control parameters for the Newton algorithm

Description

Check if the input control parameters of the quasi-Newton algorithm are allowed and set them to default values if they are not. Returns a list of well-defined control parameters.

Usage

set.control.newton(
  normalize = TRUE,
  maxiter = 500,
  stepsize = 0.01,
  eps = 1e-08,
  nafill = 1,
  tol = 1e-05,
  damping = 0.001,
  verbose = FALSE,
  frequency = 50,
  parallel = FALSE,
  nthreads = 1
)

Arguments

normalize	if TRUE, normalize U and V to uncorrelated Gaussian U and upper triangular V with positive diagonal
maxiter	maximum number of iterations
stepsize	step-size parameter scaling each IRWLS step
eps	how much shrinkage has to be introduced on extreme predictions lying outside of the data range
nafill	how frequently the NA values are filled, by default NA values are filled at each iteration of the algorithm
tol	tolerance threshold for the stopping criterion
damping	regularization parameter which is added to the Hessian to ensure numerical stability
verbose	if TRUE, print the optimization status
frequency	how often the optimization status is printed (only if verbose=TRUE
parallel	if TRUE, allows for parallel computing using the C++ library OpenMP
nthreads	number of cores to be used in parallel (only if parallel=TTUE)

Value

A list of control parameters for the quasi-Newton algorithm

Examples

library(sgdGMF)

# Empty call
set.control.newton()

# Parametrized call
set.control.newton(maxiter = 1000, stepsize = 0.01, tol = 1e-04)

sgdGMF documentation built on April 3, 2025, 7:37 p.m.