Add intercept (or constant) column
step_intercept
creates a specification of a recipe step that
will add an intercept or constant term in the first column of a data
matrix. step_intercept
has defaults to predictor role so
that it is by default called in the bake step. Be careful to avoid
unintentional transformations when calling steps with
all_predictors
.
step_intercept( recipe, ..., role = "predictor", trained = FALSE, name = "intercept", value = 1, skip = FALSE, id = rand_id("intercept") )
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
Argument ignored; included for consistency with other step specification functions. |
role |
For model terms created by this step, what analysis role should they be assigned?. By default, the function assumes that the new columns created 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. Again included for consistency. |
name |
Character name for newly added column |
value |
A numeric constant to fill the intercept column. Defaults to 1. |
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. |
An updated version of recipe
with the
new step added to the sequence of existing steps (if any).
library(modeldata) data(biomass) biomass_tr <- biomass[biomass$dataset == "Training",] biomass_te <- biomass[biomass$dataset == "Testing",] rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur, data = biomass_tr) rec_trans <- recipe(HHV ~ ., data = biomass_tr[, -(1:2)]) %>% step_intercept(value = 2) %>% step_scale(carbon) rec_obj <- prep(rec_trans, training = biomass_tr) with_intercept <- bake(rec_obj, biomass_te) with_intercept
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