This function prints the current set of variables/features and some of their characteristics.
# S3 method for recipe summary(object, original = FALSE, ...)
object | A |
---|---|
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). |
A tibble with columns variable
, type
, role
,
and source
.
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.
#> # A tibble: 4 x 4 #> variable type role source #> <chr> <chr> <chr> <chr> #> 1 Murder numeric predictor original #> 2 Assault numeric predictor original #> 3 UrbanPop numeric predictor original #> 4 Rape numeric predictor originalrec <- step_pca(rec, all_numeric(), num_comp = 3) summary(rec) # still the same since not yet trained#> # A tibble: 4 x 4 #> variable type role source #> <chr> <chr> <chr> <chr> #> 1 Murder numeric predictor original #> 2 Assault numeric predictor original #> 3 UrbanPop numeric predictor original #> 4 Rape numeric predictor original#> # A tibble: 3 x 4 #> variable type role source #> <chr> <chr> <chr> <chr> #> 1 PC1 numeric predictor derived #> 2 PC2 numeric predictor derived #> 3 PC3 numeric predictor derived