Nothing
Code
mc_cv(warpbreaks)
Output
# Monte Carlo cross-validation (0.75/0.25) with 25 resamples
# A tibble: 25 x 2
splits id
<list> <chr>
1 <split [40/14]> Resample01
2 <split [40/14]> Resample02
3 <split [40/14]> Resample03
4 <split [40/14]> Resample04
5 <split [40/14]> Resample05
6 <split [40/14]> Resample06
7 <split [40/14]> Resample07
8 <split [40/14]> Resample08
9 <split [40/14]> Resample09
10 <split [40/14]> Resample10
# i 15 more rows
Code
group_mc_cv(warpbreaks, group = "tension", prop = 0.99)
Condition
Error in `group_mc_cv()`:
! Some assessment sets contained zero rows
i Consider using a non-grouped resampling method
Code
sizes4
Output
# A tibble: 5 x 5
analysis assessment n p id
<int> <int> <int> <int> <chr>
1 37939 12061 50000 3 Resample1
2 37063 12937 50000 3 Resample2
3 37178 12822 50000 3 Resample3
4 37950 12050 50000 3 Resample4
5 37585 12415 50000 3 Resample5
Code
group_mc_cv(warpbreaks, "tension")
Output
# Group Monte Carlo cross-validation (0.75/0.25) with 25 resamples
# A tibble: 25 x 2
splits id
<list> <chr>
1 <split [36/18]> Resample01
2 <split [36/18]> Resample02
3 <split [36/18]> Resample03
4 <split [36/18]> Resample04
5 <split [36/18]> Resample05
6 <split [36/18]> Resample06
7 <split [36/18]> Resample07
8 <split [36/18]> Resample08
9 <split [36/18]> Resample09
10 <split [36/18]> Resample10
# i 15 more rows
Code
print(group_mc_cv(warpbreaks, "tension"), n = 2)
Output
# Group Monte Carlo cross-validation (0.75/0.25) with 25 resamples
# A tibble: 25 x 2
splits id
<list> <chr>
1 <split [36/18]> Resample01
2 <split [36/18]> Resample02
# i 23 more rows
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