These functions can be used to generate indexes for use with K-fold cross-validation. See the Details section for explanations.
kfold_split_random(K = 10, N = NULL)
kfold_split_stratified(K = 10, x = NULL)
kfold_split_grouped(K = 10, x = NULL)The number of folds to use.
The number of observations in the data.
A discrete variable of length N with at least K levels (unique
values). Will be coerced to a factor.
An integer vector of length N where each element is an index in 1:K.
kfold_split_random() splits the data into K groups
of equal size (or roughly equal size).
For a categorical variable x kfold_split_stratified()
splits the observations into K groups ensuring that relative
category frequencies are approximately preserved.
For a grouping variable x, kfold_split_grouped() places
all observations in x from the same group/level together in
the same fold. The selection of which groups/levels go into which
fold (relevant when when there are more groups than folds) is
randomized.
ids <- kfold_split_random(K = 5, N = 20)
print(ids)
#> [1] 2 3 1 2 1 3 3 3 2 4 2 4 1 5 5 5 1 4 4 5
table(ids)
#> ids
#> 1 2 3 4 5
#> 4 4 4 4 4
x <- sample(c(0, 1), size = 200, replace = TRUE, prob = c(0.05, 0.95))
table(x)
#> x
#> 0 1
#> 11 189
ids <- kfold_split_stratified(K = 5, x = x)
print(ids)
#> [1] 3 1 5 3 2 4 3 1 1 2 2 1 5 2 3 5 4 4 1 2 2 5 4 5 5 1 4 3 1 2 1 4 4 4 5 5 4
#> [38] 5 5 3 3 4 1 2 2 3 2 1 1 5 4 5 3 4 2 4 2 1 2 5 3 4 1 2 2 1 5 5 4 4 3 5 2 3
#> [75] 4 2 4 1 2 4 1 3 1 3 1 2 5 3 3 5 2 1 3 5 1 3 5 2 5 3 1 4 2 1 3 1 4 5 5 3 4
#> [112] 3 3 3 2 2 5 3 4 5 3 1 2 5 2 1 1 3 5 2 2 2 1 1 5 5 3 5 5 4 5 2 2 5 4 1 2 4
#> [149] 1 1 1 3 4 2 4 3 3 3 3 2 3 4 4 3 2 2 4 4 4 1 5 4 2 5 1 4 5 2 1 5 4 5 1 5 1
#> [186] 4 3 1 3 1 4 5 3 1 3 2 2 3 4 4
table(ids, x)
#> x
#> ids 0 1
#> 1 3 37
#> 2 2 38
#> 3 2 38
#> 4 2 38
#> 5 2 38
grp <- gl(n = 50, k = 15, labels = state.name)
length(grp)
#> [1] 750
head(table(grp))
#> grp
#> Alabama Alaska Arizona Arkansas California Colorado
#> 15 15 15 15 15 15
ids_10 <- kfold_split_grouped(K = 10, x = grp)
(tab_10 <- table(grp, ids_10))
#> ids_10
#> grp 1 2 3 4 5 6 7 8 9 10
#> Alabama 0 0 0 0 15 0 0 0 0 0
#> Alaska 0 0 0 0 0 0 15 0 0 0
#> Arizona 0 0 0 0 0 0 15 0 0 0
#> Arkansas 0 0 0 0 0 0 0 15 0 0
#> California 0 0 0 0 0 15 0 0 0 0
#> Colorado 0 0 0 0 0 15 0 0 0 0
#> Connecticut 15 0 0 0 0 0 0 0 0 0
#> Delaware 0 0 0 0 0 0 0 0 15 0
#> Florida 15 0 0 0 0 0 0 0 0 0
#> Georgia 0 0 0 0 0 0 0 0 0 15
#> Hawaii 0 0 0 15 0 0 0 0 0 0
#> Idaho 0 0 0 0 0 0 0 15 0 0
#> Illinois 0 15 0 0 0 0 0 0 0 0
#> Indiana 0 0 0 0 0 0 0 0 0 15
#> Iowa 0 0 0 0 0 0 15 0 0 0
#> Kansas 0 0 15 0 0 0 0 0 0 0
#> Kentucky 0 0 15 0 0 0 0 0 0 0
#> Louisiana 0 0 0 0 0 15 0 0 0 0
#> Maine 15 0 0 0 0 0 0 0 0 0
#> Maryland 0 0 0 0 0 0 0 0 15 0
#> Massachusetts 0 0 0 0 0 0 0 0 15 0
#> Michigan 0 0 0 0 0 0 0 0 15 0
#> Minnesota 15 0 0 0 0 0 0 0 0 0
#> Mississippi 0 0 0 0 0 0 0 15 0 0
#> Missouri 0 0 0 0 15 0 0 0 0 0
#> Montana 0 0 0 0 0 0 0 15 0 0
#> Nebraska 0 0 0 0 0 0 0 15 0 0
#> Nevada 0 0 0 15 0 0 0 0 0 0
#> New Hampshire 0 0 0 0 0 15 0 0 0 0
#> New Jersey 15 0 0 0 0 0 0 0 0 0
#> New Mexico 0 0 0 0 0 0 0 0 0 15
#> New York 0 0 0 0 0 15 0 0 0 0
#> North Carolina 0 0 15 0 0 0 0 0 0 0
#> North Dakota 0 0 0 0 0 0 15 0 0 0
#> Ohio 0 15 0 0 0 0 0 0 0 0
#> Oklahoma 0 0 15 0 0 0 0 0 0 0
#> Oregon 0 0 0 15 0 0 0 0 0 0
#> Pennsylvania 0 0 0 15 0 0 0 0 0 0
#> Rhode Island 0 0 0 15 0 0 0 0 0 0
#> South Carolina 0 0 0 0 15 0 0 0 0 0
#> South Dakota 0 0 0 0 0 0 15 0 0 0
#> Tennessee 0 0 15 0 0 0 0 0 0 0
#> Texas 0 0 0 0 15 0 0 0 0 0
#> Utah 0 15 0 0 0 0 0 0 0 0
#> Vermont 0 0 0 0 0 0 0 0 15 0
#> Virginia 0 0 0 0 15 0 0 0 0 0
#> Washington 0 0 0 0 0 0 0 0 0 15
#> West Virginia 0 0 0 0 0 0 0 0 0 15
#> Wisconsin 0 15 0 0 0 0 0 0 0 0
#> Wyoming 0 15 0 0 0 0 0 0 0 0
colSums(tab_10)
#> 1 2 3 4 5 6 7 8 9 10
#> 75 75 75 75 75 75 75 75 75 75
ids_9 <- kfold_split_grouped(K = 9, x = grp)
(tab_9 <- table(grp, ids_9))
#> ids_9
#> grp 1 2 3 4 5 6 7 8 9
#> Alabama 0 0 15 0 0 0 0 0 0
#> Alaska 0 0 15 0 0 0 0 0 0
#> Arizona 0 0 0 0 0 0 0 15 0
#> Arkansas 0 0 15 0 0 0 0 0 0
#> California 0 0 0 0 0 0 0 15 0
#> Colorado 15 0 0 0 0 0 0 0 0
#> Connecticut 0 0 0 15 0 0 0 0 0
#> Delaware 0 15 0 0 0 0 0 0 0
#> Florida 0 0 0 0 0 0 0 0 15
#> Georgia 0 0 15 0 0 0 0 0 0
#> Hawaii 0 0 0 15 0 0 0 0 0
#> Idaho 0 0 15 0 0 0 0 0 0
#> Illinois 0 0 0 0 0 15 0 0 0
#> Indiana 0 0 0 0 0 0 15 0 0
#> Iowa 0 0 0 0 0 0 0 0 15
#> Kansas 0 0 0 0 0 0 15 0 0
#> Kentucky 0 0 0 0 15 0 0 0 0
#> Louisiana 15 0 0 0 0 0 0 0 0
#> Maine 0 15 0 0 0 0 0 0 0
#> Maryland 0 0 0 15 0 0 0 0 0
#> Massachusetts 15 0 0 0 0 0 0 0 0
#> Michigan 0 0 0 0 0 0 0 15 0
#> Minnesota 0 0 0 0 0 15 0 0 0
#> Mississippi 15 0 0 0 0 0 0 0 0
#> Missouri 0 0 0 0 0 15 0 0 0
#> Montana 0 15 0 0 0 0 0 0 0
#> Nebraska 0 0 0 15 0 0 0 0 0
#> Nevada 0 0 0 0 15 0 0 0 0
#> New Hampshire 0 0 0 0 0 0 15 0 0
#> New Jersey 15 0 0 0 0 0 0 0 0
#> New Mexico 0 0 0 0 0 0 15 0 0
#> New York 0 0 0 0 0 15 0 0 0
#> North Carolina 0 15 0 0 0 0 0 0 0
#> North Dakota 0 0 0 0 0 0 15 0 0
#> Ohio 0 0 0 0 0 15 0 0 0
#> Oklahoma 0 0 0 0 15 0 0 0 0
#> Oregon 0 0 0 0 0 0 0 15 0
#> Pennsylvania 0 0 0 0 15 0 0 0 0
#> Rhode Island 0 0 15 0 0 0 0 0 0
#> South Carolina 0 0 0 0 0 0 0 0 15
#> South Dakota 0 0 0 0 0 0 0 0 15
#> Tennessee 0 15 0 0 0 0 0 0 0
#> Texas 0 0 0 0 15 0 0 0 0
#> Utah 0 0 0 15 0 0 0 0 0
#> Vermont 0 0 0 0 15 0 0 0 0
#> Virginia 0 15 0 0 0 0 0 0 0
#> Washington 15 0 0 0 0 0 0 0 0
#> West Virginia 0 0 0 15 0 0 0 0 0
#> Wisconsin 0 0 0 0 0 0 0 0 15
#> Wyoming 0 0 0 0 0 0 0 15 0
colSums(tab_9)
#> 1 2 3 4 5 6 7 8 9
#> 90 90 90 90 90 75 75 75 75