The problem
I'm having trouble understanding why grid_latin_hypercube and grid_max_entropy only return objects of class tibble (and data frame, etc..) when grid_regular and grid_random return objects with custom classes of param_grid. I'm planing to create methods for tuning grids and I stumbled into this. Is this a design choice?
Have you considered adding a custom class to these two tuning grids as well?
Reproducible example
library(dials)
#> Loading required package: scales
class(grid_latin_hypercube(penalty(), mixture()))
#> [1] "tbl_df" "tbl" "data.frame"
class(grid_max_entropy(penalty(), mixture()))
#> [1] "tbl_df" "tbl" "data.frame"
# Whereas grid_regular and grid_random do have
class(grid_random(penalty(), mixture()))
#> [1] "grid_random" "param_grid" "tbl_df" "tbl" "data.frame"
class(grid_regular(penalty(), mixture()))
#> [1] "grid_regular" "param_grid" "tbl_df" "tbl" "data.frame"
The problem
I'm having trouble understanding why
grid_latin_hypercubeandgrid_max_entropyonly return objects of classtibble(and data frame, etc..) whengrid_regularandgrid_randomreturn objects with custom classes ofparam_grid. I'm planing to create methods for tuning grids and I stumbled into this. Is this a design choice?Have you considered adding a custom class to these two tuning grids as well?
Reproducible example