step_spatialsign is a specification of a recipe
step that will convert numeric data into a projection on to a
step_spatialsign( recipe, ..., role = "predictor", na_rm = TRUE, trained = FALSE, columns = NULL, skip = FALSE, id = rand_id("spatialsign") ) # S3 method for step_spatialsign tidy(x, ...)
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 will be used for the normalization. See
For model terms created by this step, what analysis role should they be assigned?
A logical: should missing data be removed from the norm computation?
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
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). For the
tidy method, a tibble with columns
is the columns that will be affected.
The spatial sign transformation projects the variables
onto a unit sphere and is related to global contrast
normalization. The spatial sign of a vector
The variables should be centered and scaled prior to the computations.
Serneels, S., De Nolf, E., and Van Espen, P. (2006). Spatial sign preprocessing: a simple way to impart moderate robustness to multivariate estimators. Journal of Chemical Information and Modeling, 46(3), 1402-1409.
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) ss_trans <- rec %>% step_center(carbon, hydrogen) %>% step_scale(carbon, hydrogen) %>% step_spatialsign(carbon, hydrogen) ss_obj <- prep(ss_trans, training = biomass_tr) transformed_te <- bake(ss_obj, biomass_te) plot(biomass_te$carbon, biomass_te$hydrogen)plot(transformed_te$carbon, transformed_te$hydrogen)tidy(ss_trans, number = 3)#> # A tibble: 2 x 2 #> terms id #> <chr> <chr> #> 1 carbon spatialsign_rfFce #> 2 hydrogen spatialsign_rfFcetidy(ss_obj, number = 3)#> # A tibble: 2 x 2 #> terms id #> <chr> <chr> #> 1 carbon spatialsign_rfFce #> 2 hydrogen spatialsign_rfFce