dot-loss: Loss

In rauschenberger/starnet: Stacked Elastic Net

Loss

Description

Calculate loss from predicted and observed values

Usage

.loss(y, x, family, type.measure, foldid = NULL, grouped = TRUE)

Arguments

y	observed values: numeric vector of length n
x	predicted values: numeric vector of length n
family	character "gaussian", "binomial", "poisson", "mgaussian", or "multinomial" (to implement: "cox")
type.measure	character "deviance", "mse", "mae", "class", or "auc"
foldid	fold identifiers: integer vector of length n, or NULL
grouped	logical (for "cox" only)

Examples

NA

rauschenberger/starnet documentation built on July 4, 2025, 1:28 p.m.