Expose pool argument across resampling functions

[juliasilge]

This PR closes #211 by exposing the pool argument to user-facing functions such as vfold_cv(), mc_cv(), and bootstraps().

library(tidyverse)
library(rsample)

df <- tibble(x = rnorm(60), label = rep(letters[1:12], each = 5))

mc_cv(df, v = 3, strata = label)
#> Warning: Too little data to stratify. Unstratified resampling
#> # Monte Carlo cross-validation (0.75/0.25) with 25 resamples  using stratification 
#> # A tibble: 25 x 2
#>    splits          id        
#>    <list>          <chr>     
#>  1 <split [45/15]> Resample01
#>  2 <split [45/15]> Resample02
#>  3 <split [45/15]> Resample03
#>  4 <split [45/15]> Resample04
#>  5 <split [45/15]> Resample05
#>  6 <split [45/15]> Resample06
#>  7 <split [45/15]> Resample07
#>  8 <split [45/15]> Resample08
#>  9 <split [45/15]> Resample09
#> 10 <split [45/15]> Resample10
#> # … with 15 more rows
mc_cv(df, v = 3, strata = label, pool = 0.05)
#> Warning: Stratifying groups that make up 5% of the data may be statistically risky.
#> Consider increasing `pool` to at least 0.1
#> # Monte Carlo cross-validation (0.75/0.25) with 25 resamples  using stratification 
#> # A tibble: 25 x 2
#>    splits          id        
#>    <list>          <chr>     
#>  1 <split [36/24]> Resample01
#>  2 <split [36/24]> Resample02
#>  3 <split [36/24]> Resample03
#>  4 <split [36/24]> Resample04
#>  5 <split [36/24]> Resample05
#>  6 <split [36/24]> Resample06
#>  7 <split [36/24]> Resample07
#>  8 <split [36/24]> Resample08
#>  9 <split [36/24]> Resample09
#> 10 <split [36/24]> Resample10
#> # … with 15 more rows

^{Created on 2021-03-09 by the reprex package (v1.0.0)}

[juliasilge]

I know you have ambivalence about this @topepo but take a look and let's think about what we want to say in the warning.

Right now the warning gets triggered if pool is less than 0.1 and any of the groups turns out to be less than 10% of the sample.

[github-actions]

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