rapid_cv: Rapid cross-validation without removing samples
In neyhartj/miscRutils: My collection of useful R functions.
rapid_cv R Documentation
Rapid cross-validation without removing samples
Description
Implements cross-validation according to Gianola and Schon 2016. Returns
RMSE and r-squared
Usage
rapid_cv(object, index, rapid = TRUE)
Arguments
object
A fitted model object
index
A list of indices for leave-n-out cross-validation (i.e. the
training set)
rapid
Logical; should the rapid method be used?
Examples
fit <- lm(Sepal.Length ~ ., iris)
indices <- lapply(X = crossv_loo_grouped(group_by(iris, Species))$train, "[[", "idx")
neyhartj/miscRutils documentation built on Jan. 17, 2024, 11:15 a.m.
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| rapid_cv | R Documentation |
Rapid cross-validation without removing samples
Description
Implements cross-validation according to Gianola and Schon 2016. Returns RMSE and r-squared
Usage
rapid_cv(object, index, rapid = TRUE)
Arguments
object |
A fitted model object |
index |
A list of indices for leave-n-out cross-validation (i.e. the training set) |
rapid |
Logical; should the rapid method be used? |
Examples
fit <- lm(Sepal.Length ~ ., iris)
indices <- lapply(X = crossv_loo_grouped(group_by(iris, Species))$train, "[[", "idx")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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