Description Usage Arguments Details Value Examples
'nested_cv' can be used to take the results of one resampling procedure and conduct further resamples within each split. Any type of resampling used in 'rsample' can be used.
1 |
data |
A data frame. |
outside |
The initial resampling specification. This can be an already created object or an expression of a new object (see the examples below). If the latter is used, the 'data' argument does not need to be specified and, if it is given, will be ignored. |
inside |
An expression for the type of resampling to be conducted within the initial procedure. |
It is a bad idea to use bootstrapping as the outer resampling procedure (see the example below)
An tibble with classe 'nested_cv' and any other classes that outer resampling process normally contains. The results include a column for the outer data split objects, one or more 'id' columns, and a column of nested tibbles called 'inner_resamples' with the additional resamples.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## Using expressions for the resampling procedures:
nested_cv(mtcars, outside = vfold_cv(v = 3), inside = bootstraps(times = 5))
## Using an existing object:
folds <- vfold_cv(mtcars)
nested_cv(mtcars, folds, inside = bootstraps(times = 5))
## The dangers of outer bootstraps:
set.seed(2222)
bad_idea <- nested_cv(mtcars,
outside = bootstraps(times = 5),
inside = vfold_cv(v = 3))
first_outer_split <- bad_idea$splits[[1]]
outer_analysis <- as.data.frame(first_outer_split)
sum(grepl("Volvo 142E", rownames(outer_analysis)))
## For the 3-fold CV used inside of each bootstrap, how are the replicated
## `Volvo 142E` data partitioned?
first_inner_split <- bad_idea$inner_resamples[[1]]$splits[[1]]
inner_analysis <- as.data.frame(first_inner_split)
inner_assess <- as.data.frame(first_inner_split, data = "assessment")
sum(grepl("Volvo 142E", rownames(inner_analysis)))
sum(grepl("Volvo 142E", rownames(inner_assess)))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.