step_collapse_stringdist
creates a specification of a recipe step
that will collapse factor levels that have a low stringdist between them.
Usage
step_collapse_stringdist(
recipe,
...,
role = NA,
trained = FALSE,
distance = NULL,
results = NULL,
columns = NULL,
skip = FALSE,
id = rand_id("collapse_stringdist")
)
Arguments
- recipe
A recipe object. The step will be added to the sequence of operations for this recipe.
- ...
One or more selector functions to choose which variables are affected by the step. See
selections()
for more details. For thetidy
method, these are not currently used.- role
Not used by this step since no new variables are created.
- trained
A logical to indicate if the quantities for preprocessing have been estimated.
- distance
Integer, value to determine which strings should be collapsed with which. The value is being used inclusive, so
2
will collapse levels that have a string distance between them of 2 or lower.- results
A list denoting the way the labels should be collapses is stored here once this preprocessing step has be trained by
prep()
.- columns
A character string of variable names that will be populated (eventually) by the
terms
argument.- skip
A logical. Should the step be skipped when the recipe is baked by
bake()
? While all operations are baked whenprep()
is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when usingskip = TRUE
as it may affect the computations for subsequent operations.- id
A character string that is unique to this step to identify it.
Value
An updated version of recipe
with the new step
added to the sequence of existing steps (if any). For the
tidy
method, a tibble with columns terms
(the
columns that will be affected) and base
.
Tidying
When you tidy()
this step, a tibble with columns "terms"
(the column being modified), "from"
(the old levels), "to"
(the new
levels), and "id"
.
Examples
library(recipes)
library(tibble)
data0 <- tibble(
x1 = c("a", "b", "d", "e", "sfgsfgsd", "hjhgfgjgr"),
x2 = c("ak", "b", "djj", "e", "hjhgfgjgr", "hjhgfgjgr")
)
rec <- recipe(~., data = data0) %>%
step_collapse_stringdist(all_predictors(), distance = 1) %>%
prep()
rec %>%
bake(new_data = NULL)
#> # A tibble: 6 × 2
#> x1 x2
#> <fct> <fct>
#> 1 a ak
#> 2 a b
#> 3 a djj
#> 4 a b
#> 5 sfgsfgsd hjhgfgjgr
#> 6 hjhgfgjgr hjhgfgjgr
tidy(rec, 1)
#> # A tibble: 11 × 4
#> terms from to id
#> <chr> <chr> <chr> <chr>
#> 1 x1 a a collapse_stringdist_MYS4w
#> 2 x1 b a collapse_stringdist_MYS4w
#> 3 x1 d a collapse_stringdist_MYS4w
#> 4 x1 e a collapse_stringdist_MYS4w
#> 5 x1 hjhgfgjgr hjhgfgjgr collapse_stringdist_MYS4w
#> 6 x1 sfgsfgsd sfgsfgsd collapse_stringdist_MYS4w
#> 7 x2 ak ak collapse_stringdist_MYS4w
#> 8 x2 b b collapse_stringdist_MYS4w
#> 9 x2 e b collapse_stringdist_MYS4w
#> 10 x2 djj djj collapse_stringdist_MYS4w
#> 11 x2 hjhgfgjgr hjhgfgjgr collapse_stringdist_MYS4w
rec <- recipe(~., data = data0) %>%
step_collapse_stringdist(all_predictors(), distance = 2) %>%
prep()
rec %>%
bake(new_data = NULL)
#> # A tibble: 6 × 2
#> x1 x2
#> <fct> <fct>
#> 1 a ak
#> 2 a ak
#> 3 a djj
#> 4 a ak
#> 5 sfgsfgsd hjhgfgjgr
#> 6 hjhgfgjgr hjhgfgjgr
tidy(rec, 1)
#> # A tibble: 11 × 4
#> terms from to id
#> <chr> <chr> <chr> <chr>
#> 1 x1 a a collapse_stringdist_rsPrv
#> 2 x1 b a collapse_stringdist_rsPrv
#> 3 x1 d a collapse_stringdist_rsPrv
#> 4 x1 e a collapse_stringdist_rsPrv
#> 5 x1 hjhgfgjgr hjhgfgjgr collapse_stringdist_rsPrv
#> 6 x1 sfgsfgsd sfgsfgsd collapse_stringdist_rsPrv
#> 7 x2 ak ak collapse_stringdist_rsPrv
#> 8 x2 b ak collapse_stringdist_rsPrv
#> 9 x2 e ak collapse_stringdist_rsPrv
#> 10 x2 djj djj collapse_stringdist_rsPrv
#> 11 x2 hjhgfgjgr hjhgfgjgr collapse_stringdist_rsPrv