View source: R/poly_bernstein.R
step_poly_bernstein | R Documentation |
step_poly_bernstein()
creates a specification of a recipe step that
creates Bernstein polynomial features.
step_poly_bernstein(
recipe,
...,
role = NA,
trained = FALSE,
degree = 10,
complete_set = FALSE,
options = NULL,
keep_original_cols = FALSE,
results = NULL,
skip = FALSE,
id = rand_id("poly_bernstein")
)
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
One or more selector functions to choose variables
for this step. See |
role |
For model terms created by this step, what analysis role should they be assigned? By default, the new columns created by this step from the original variables will be used as predictors in a model. |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
degree |
The degrees of the polynomial. As the degrees for a polynomial increase, more flexible and complex curves can be generated. |
complete_set |
If |
options |
A list of options for |
keep_original_cols |
A logical to keep the original variables in the
output. Defaults to |
results |
A list of objects created once the step has been trained. |
skip |
A logical. Should the step be skipped when the
recipe is baked by |
id |
A character string that is unique to this step to identify it. |
Polynomial transformations take a numeric column and create multiple features that, when used in a model, can estimate nonlinear trends between the column and some outcome. The degrees of freedom determines how many new features are added to the data.
If the spline expansion fails for a selected column, the step will
remove that column's results (but will retain the original data). Use the
tidy()
method to determine which columns were used.
An object with classes "step_poly_bernstein"
and "step"
.
When you tidy()
this step, a tibble is returned with
columns terms
and id
:
character, the selectors or variables selected
character, id of this step
This step has 1 tuning parameters:
degree
: Polynomial Degree (type: integer, default: 10)
The underlying operation does not allow for case weights.
splines2::bernsteinPoly()
library(tidyr)
library(dplyr)
library(ggplot2)
data(ames, package = "modeldata")
spline_rec <- recipe(Sale_Price ~ Longitude, data = ames) %>%
step_poly_bernstein(Longitude, degree = 6, keep_original_cols = TRUE) %>%
prep()
tidy(spline_rec, number = 1)
# Show where each feature is active
spline_rec %>%
bake(new_data = NULL,-Sale_Price) %>%
pivot_longer(c(starts_with("Longitude_")), names_to = "feature", values_to = "value") %>%
mutate(feature = gsub("Longitude_", "feature ", feature)) %>%
filter(value > 0) %>%
ggplot(aes(x = Longitude, y = value)) +
geom_line() +
facet_wrap(~ feature)
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