Inverse Logit TransformationSource:
step_invlogit creates a specification of a recipe
step that will transform the data from real values to be between
zero and one.
step_invlogit( recipe, ..., role = NA, trained = FALSE, columns = NULL, skip = FALSE, id = rand_id("invlogit") )
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
selections()for more details.
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A character string of variable names that will be populated (eventually) by the
A logical. Should the step be skipped when the recipe is baked by
bake()? While all operations are baked when
prep()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 using
skip = TRUEas it may affect the computations for subsequent operations.
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 any existing operations.
The inverse logit transformation takes values on the
real line and translates them to be between zero and one using
f(x) = 1/(1+exp(-x)).
tidy() this step, a tibble with columns
terms (the columns that will be affected) is returned.
data(biomass, package = "modeldata") biomass_tr <- biomass[biomass$dataset == "Training", ] biomass_te <- biomass[biomass$dataset == "Testing", ] rec <- recipe( HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur, data = biomass_tr ) ilogit_trans <- rec %>% step_center(carbon, hydrogen) %>% step_scale(carbon, hydrogen) %>% step_invlogit(carbon, hydrogen) ilogit_obj <- prep(ilogit_trans, training = biomass_tr) transformed_te <- bake(ilogit_obj, biomass_te) plot(biomass_te$carbon, transformed_te$carbon)