predict.multialpha.repeated.cv.glmnet: predict.multialpha.repeated.cv.glmnet

In AndrewLawrence/dCVnet: doubly cross-validated elastic-net regularised generalised linear models

predict.multialpha.repeated.cv.glmnet

Description

obtain predictions from a multialpha.repeated.cv.glmnet object. Uses the 'best' alpha & lambda hyperparameters determined by the internal cross-validation results. For lambda this will be lambda.min or lambda.1se (determined at model runtime) unless requested otherwise.

Usage

## S3 method for class 'multialpha.repeated.cv.glmnet'
predict(object, newx, alpha = NULL, s = NULL, ...)

Arguments

object	a a multialpha.repeated.cv.glmnet object.
newx	matrix of new values for x at which predictions are required. Note: no impact when type is "coefficients", "class" or "nonzero".
alpha	the penalty type alpha at which prediction is required. Leave NULL to use the cv-optimised value.
s	The penalty amount lambda at which prediction is required. Leave NULL to use the cv-optimised value.
...	passed to predict.glmnet

See Also

predict.cv.glmnet, predict.glmnet

AndrewLawrence/dCVnet documentation built on Sept. 24, 2024, 5:24 a.m.