setup_GLMNET: Setup GLMNET Hyperparameters

In egenn/rtemis: Machine Learning and Visualization

Setup GLMNET Hyperparameters

Description

Setup hyperparameters for GLMNET training.

Usage

setup_GLMNET(
  alpha = 1,
  family = NULL,
  offset = NULL,
  which_lambda_cv = "lambda.1se",
  nlambda = 100L,
  lambda = NULL,
  penalty_factor = NULL,
  standardize = TRUE,
  intercept = TRUE,
  ifw = FALSE
)

Arguments

alpha	(Tunable) Numeric: Mixing parameter.
family	Character: Family for GLMNET.
offset	Numeric: Offset for GLMNET.
which_lambda_cv	Character: Which lambda to use for prediction: "lambda.1se" or "lambda.min"
nlambda	Positive integer: Number of lambda values.
lambda	Numeric: Lambda values.
penalty_factor	Numeric: Penalty factor for each feature.
standardize	Logical: If TRUE, standardize features.
intercept	Logical: If TRUE, include intercept.
ifw	Logical: If TRUE, use Inverse Frequency Weighting in classification.

Details

Get more information from glmnet::glmnet.

Value

GLMNETHyperparameters object.

Author(s)

EDG

egenn/rtemis documentation built on June 14, 2025, 11:54 p.m.