This function prints the current set of variables/features and some of their characteristics.
Usage
# S3 method for recipe
summary(object, original = FALSE, ...)Arguments
- object
A
recipeobject- original
A logical: show the current set of variables or the original set when the recipe was defined.
- ...
further arguments passed to or from other methods (not currently used).
Value
A tibble with columns variable, type, role,
and source. When original = TRUE, an additional column is included
named required_to_bake (based on the results of
update_role_requirements()).
Details
Note that, until the recipe has been trained, the current and original variables are the same.
It is possible for variables to have multiple roles by adding them with
add_role(). If a variable has multiple roles, it will have more than one
row in the summary tibble.
Examples
rec <- recipe(~., data = USArrests)
summary(rec)
#> # A tibble: 4 × 4
#> variable type role source
#> <chr> <list> <chr> <chr>
#> 1 Murder <chr [2]> predictor original
#> 2 Assault <chr [2]> predictor original
#> 3 UrbanPop <chr [2]> predictor original
#> 4 Rape <chr [2]> predictor original
rec <- step_pca(rec, all_numeric(), num_comp = 3)
summary(rec) # still the same since not yet trained
#> # A tibble: 4 × 4
#> variable type role source
#> <chr> <list> <chr> <chr>
#> 1 Murder <chr [2]> predictor original
#> 2 Assault <chr [2]> predictor original
#> 3 UrbanPop <chr [2]> predictor original
#> 4 Rape <chr [2]> predictor original
rec <- prep(rec, training = USArrests)
summary(rec)
#> # A tibble: 3 × 4
#> variable type role source
#> <chr> <list> <chr> <chr>
#> 1 PC1 <chr [2]> predictor derived
#> 2 PC2 <chr [2]> predictor derived
#> 3 PC3 <chr [2]> predictor derived