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glmnet.control

internal glmnet parameters


Description

View and/or change the factory default parameters in glmnet

Usage

glmnet.control(
  fdev = 1e-05,
  devmax = 0.999,
  eps = 1e-06,
  big = 9.9e+35,
  mnlam = 5,
  pmin = 1e-09,
  exmx = 250,
  prec = 1e-10,
  mxit = 100,
  itrace = 0,
  epsnr = 1e-06,
  mxitnr = 25,
  factory = FALSE
)

Arguments

fdev

minimum fractional change in deviance for stopping path; factory default = 1.0e-5

devmax

maximum fraction of explained deviance for stopping path; factory default = 0.999

eps

minimum value of lambda.min.ratio (see glmnet); factory default= 1.0e-6

big

large floating point number; factory default = 9.9e35. Inf in definition of upper.limit is set to big

mnlam

minimum number of path points (lambda values) allowed; factory default = 5

pmin

minimum probability for any class. factory default = 1.0e-9. Note that this implies a pmax of 1-pmin.

exmx

maximum allowed exponent. factory default = 250.0

prec

convergence threshold for multi response bounds adjustment solution. factory default = 1.0e-10

mxit

maximum iterations for multiresponse bounds adjustment solution. factory default = 100

itrace

If 1 then progress bar is displayed when running glmnet and cv.glmnet. factory default = 0

epsnr

convergence threshold for glmnet.fit. factory default = 1.0e-6

mxitnr

maximum iterations for the IRLS loop in glmnet.fit. factory default = 25

factory

If TRUE, reset all the parameters to the factory default; default is FALSE

Details

If called with no arguments, glmnet.control() returns a list with the current settings of these parameters. Any arguments included in the call sets those parameters to the new values, and then silently returns. The values set are persistent for the duration of the R session.

Value

A list with named elements as in the argument list

Author(s)

Jerome Friedman, Kenneth Tay, Trevor Hastie
Maintainer: Trevor Hastie hastie@stanford.edu

See Also

glmnet

Examples

glmnet.control(fdev = 0)  #continue along path even though not much changes
glmnet.control()  # view current settings
glmnet.control(factory = TRUE)  # reset all the parameters to their default

glmnet

Lasso and Elastic-Net Regularized Generalized Linear Models

v4.1-1
GPL-2
Authors
Jerome Friedman [aut], Trevor Hastie [aut, cre], Rob Tibshirani [aut], Balasubramanian Narasimhan [aut], Kenneth Tay [aut], Noah Simon [aut], Junyang Qian [ctb]
Initial release
2021-02-17

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