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,
method = "osa",
options = list(),
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.- method
Character, method for distance calculation. The default is
"osa"
, see stringdist::stringdist-metrics.- options
List, other arguments passed to
stringdist::stringdistmatrix()
such asweight
,q
,p
, andbt
, that are used for different values ofmethod
.- 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_F7qKG
#> 2 x1 b a collapse_stringdist_F7qKG
#> 3 x1 d a collapse_stringdist_F7qKG
#> 4 x1 e a collapse_stringdist_F7qKG
#> 5 x1 hjhgfgjgr hjhgfgjgr collapse_stringdist_F7qKG
#> 6 x1 sfgsfgsd sfgsfgsd collapse_stringdist_F7qKG
#> 7 x2 ak ak collapse_stringdist_F7qKG
#> 8 x2 b b collapse_stringdist_F7qKG
#> 9 x2 e b collapse_stringdist_F7qKG
#> 10 x2 djj djj collapse_stringdist_F7qKG
#> 11 x2 hjhgfgjgr hjhgfgjgr collapse_stringdist_F7qKG
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_m6FIF
#> 2 x1 b a collapse_stringdist_m6FIF
#> 3 x1 d a collapse_stringdist_m6FIF
#> 4 x1 e a collapse_stringdist_m6FIF
#> 5 x1 hjhgfgjgr hjhgfgjgr collapse_stringdist_m6FIF
#> 6 x1 sfgsfgsd sfgsfgsd collapse_stringdist_m6FIF
#> 7 x2 ak ak collapse_stringdist_m6FIF
#> 8 x2 b ak collapse_stringdist_m6FIF
#> 9 x2 e ak collapse_stringdist_m6FIF
#> 10 x2 djj djj collapse_stringdist_m6FIF
#> 11 x2 hjhgfgjgr hjhgfgjgr collapse_stringdist_m6FIF