tests/testthat/_snaps/vfold.md

In tidymodels/rsample: General Resampling Infrastructure

strata

Code
  rs4 <- vfold_cv(mlc_churn, strata = state, pool = 0.01)
Condition
  Warning:
  Stratifying groups that make up 1% of the data may be statistically risky.
  i Consider increasing `pool` to at least 0.1.

strata arg is checked

Code
  vfold_cv(iris, strata = iris$Species)
Condition
  Error in `vfold_cv()`:
  ! Can't select columns that don't exist.
  x Columns `setosa`, `setosa`, `setosa`, `setosa`, `setosa`, etc. don't exist.

Code
  vfold_cv(iris, strata = c("Species", "Sepal.Width"))
Condition
  Error in `vfold_cv()`:
  ! `strata` must be a single string or `NULL`, not a character vector.

Code
  vfold_cv(iris, strata = NA)
Condition
  Error in `vfold_cv()`:
  ! Selections can't have missing values.

Code
  vfold_cv(dat, strata = b)
Condition
  Error in `vfold_cv()`:
  ! strata cannot be a <Surv> object.
  i Use the time or event variable directly.

v arg is checked

Code
  vfold_cv(iris, v = -500)
Condition
  Error in `vfold_cv()`:
  ! `v` must be a whole number larger than or equal to 2, not the number -500.

Code
  vfold_cv(iris, v = 1)
Condition
  Error in `vfold_cv()`:
  ! `v` must be a whole number larger than or equal to 2, not the number 1.

Code
  vfold_cv(iris, v = NULL)
Condition
  Error in `vfold_cv()`:
  ! `v` must be a whole number, not `NULL`.

Code
  vfold_cv(iris, v = 500)
Condition
  Error in `vfold_cv()`:
  ! The number of rows is less than `v` = 500.

Code
  vfold_cv(mtcars, v = nrow(mtcars))
Condition
  Error in `vfold_cv()`:
  ! Leave-one-out cross-validation is not supported by this function.
  x You set `v` to `nrow(data)`, which would result in a leave-one-out cross-validation.
  i Use `loo_cv()` in this case.

repeats arg is checked

Code
  vfold_cv(iris, v = 150, repeats = 2)
Condition
  Error in `vfold_cv()`:
  ! Repeated resampling when `v` is 150 would create identical resamples.

Code
  vfold_cv(Orange, repeats = 0)
Condition
  Error in `vfold_cv()`:
  ! `repeats` must be a whole number larger than or equal to 1, not the number 0.

Code
  vfold_cv(Orange, repeats = NULL)
Condition
  Error in `vfold_cv()`:
  ! `repeats` must be a whole number, not `NULL`.

printing

Code
  vfold_cv(mtcars)
Output
  #  10-fold cross-validation 
  # A tibble: 10 x 2
     splits         id    
     <list>         <chr> 
   1 <split [28/4]> Fold01
   2 <split [28/4]> Fold02
   3 <split [29/3]> Fold03
   4 <split [29/3]> Fold04
   5 <split [29/3]> Fold05
   6 <split [29/3]> Fold06
   7 <split [29/3]> Fold07
   8 <split [29/3]> Fold08
   9 <split [29/3]> Fold09
  10 <split [29/3]> Fold10

grouping -- bad args

Code
  group_vfold_cv(warpbreaks, group = warpbreaks$tension)
Condition
  Error in `validate_group()`:
  ! Can't select columns that don't exist.
  x Columns `L`, `L`, `L`, `L`, `L`, etc. don't exist.

Code
  group_vfold_cv(warpbreaks, group = c("tension", "wool"))
Condition
  Error in `group_vfold_cv()`:
  ! `group` must be a single string, not a character vector.

Code
  group_vfold_cv(warpbreaks, group = "tensio")
Condition
  Error in `validate_group()`:
  ! Can't select columns that don't exist.
  x Column `tensio` doesn't exist.

Code
  group_vfold_cv(warpbreaks)
Condition
  Error in `group_vfold_cv()`:
  ! `group` must be a single string, not `NULL`.

Code
  group_vfold_cv(warpbreaks, group = "tension", v = 10)
Condition
  Error in `group_vfold_cv()`:
  ! The number of groups is less than `v` = 10.

Code
  group_vfold_cv(dat1, c, v = 4, repeats = 4)
Condition
  Error in `group_vfold_cv()`:
  ! Repeated resampling when `v` is 4 would create identical resamples.

Code
  group_vfold_cv(dat1, c, repeats = 4)
Condition
  Error in `group_vfold_cv()`:
  ! Repeated resampling when `v` is "NULL" would create identical resamples.

Code
  group_vfold_cv(Orange, v = 1, group = "Tree")
Condition
  Error in `group_vfold_cv()`:
  ! `v` must be a whole number larger than or equal to 2, not the number 1.

grouping -- other balance methods

Code
  rs1
Output
  # Group 5-fold cross-validation 
  # A tibble: 5 x 2
    splits             id       
    <list>             <chr>    
  1 <split [2364/566]> Resample1
  2 <split [2371/559]> Resample2
  3 <split [2360/570]> Resample3
  4 <split [2278/652]> Resample4
  5 <split [2347/583]> Resample5

grouping -- strata

Code
  sizes4
Output
  # A tibble: 5 x 5
    analysis assessment      n     p id       
       <int>      <int>  <int> <int> <chr>    
  1    80004      19996 100000     3 Resample1
  2    79850      20150 100000     3 Resample2
  3    79912      20088 100000     3 Resample3
  4    80131      19869 100000     3 Resample4
  5    80103      19897 100000     3 Resample5

Code
  group_vfold_cv(sample_data, group, strata = outcome)
Condition
  Warning in `group_vfold_cv()`:
  Leaving `v = NULL` while using stratification will set `v` to the number of groups present in the least common stratum.
  i Set `v` explicitly to override this warning.
Output
  # Group 30-fold cross-validation 
  # A tibble: 30 x 2
     splits               id        
     <list>               <chr>     
   1 <split [96070/3930]> Resample01
   2 <split [95898/4102]> Resample02
   3 <split [96079/3921]> Resample03
   4 <split [96008/3992]> Resample04
   5 <split [95982/4018]> Resample05
   6 <split [95955/4045]> Resample06
   7 <split [96025/3975]> Resample07
   8 <split [96053/3947]> Resample08
   9 <split [96030/3970]> Resample09
  10 <split [96069/3931]> Resample10
  # i 20 more rows

Code
  sizes5
Output
  # A tibble: 5 x 5
    analysis assessment      n     p id       
       <int>      <int>  <int> <int> <chr>    
  1    80096      19904 100000     3 Resample1
  2    79962      20038 100000     3 Resample2
  3    79928      20072 100000     3 Resample3
  4    80058      19942 100000     3 Resample4
  5    79956      20044 100000     3 Resample5

Code
  group_vfold_cv(sample_data, group, strata = outcome)
Condition
  Warning in `group_vfold_cv()`:
  Leaving `v = NULL` while using stratification will set `v` to the number of groups present in the least common stratum.
  i Set `v` explicitly to override this warning.
Output
  # Group 30-fold cross-validation 
  # A tibble: 30 x 2
     splits               id        
     <list>               <chr>     
   1 <split [95985/4015]> Resample01
   2 <split [95983/4017]> Resample02
   3 <split [96052/3948]> Resample03
   4 <split [95867/4133]> Resample04
   5 <split [96056/3944]> Resample05
   6 <split [95956/4044]> Resample06
   7 <split [95975/4025]> Resample07
   8 <split [96062/3938]> Resample08
   9 <split [95932/4068]> Resample09
  10 <split [96051/3949]> Resample10
  # i 20 more rows

grouping fails for strata not constant across group members

Code
  group_vfold_cv(sample_data, group, v = 5, strata = outcome)
Condition
  Error in `group_vfold_cv()`:
  ! strata must be constant across all members of each group.

grouping -- printing

Code
  group_vfold_cv(warpbreaks, "tension")
Output
  # Group 3-fold cross-validation 
  # A tibble: 3 x 2
    splits          id       
    <list>          <chr>    
  1 <split [36/18]> Resample1
  2 <split [36/18]> Resample2
  3 <split [36/18]> Resample3

grouping -- printing with ...

Code
  print(group_vfold_cv(warpbreaks, "tension"), n = 2)
Output
  # Group 3-fold cross-validation 
  # A tibble: 3 x 2
    splits          id       
    <list>          <chr>    
  1 <split [36/18]> Resample1
  2 <split [36/18]> Resample2
  # i 1 more row

tidymodels/rsample documentation built on Sept. 29, 2024, 10:48 p.m.