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.