recipes: step_spatialsign – R documentation

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step_spatialsign

Spatial Sign Preprocessing

Description

step_spatialsign is a specification of a recipe step that will convert numeric data into a projection on to a unit sphere.

Usage

step_spatialsign(
  recipe,
  ...,
  role = "predictor",
  na_rm = TRUE,
  trained = FALSE,
  columns = NULL,
  skip = FALSE,
  id = rand_id("spatialsign")
)

## S3 method for class 'step_spatialsign'
tidy(x, ...)

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 will be used for the normalization. See `selections()` for more details. For the `tidy` method, these are not currently used.
`role`	For model terms created by this step, what analysis role should they be assigned?
`na_rm`	A logical: should missing data be removed from the norm computation?
`trained`	A logical to indicate if the quantities for preprocessing have been estimated.
`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.recipe()`? While all operations are baked when `prep.recipe()` 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 = TRUE` as it may affect the computations for subsequent operations
`id`	A character string that is unique to this step to identify it.
`x`	A `step_spatialsign` object.

Details

The spatial sign transformation projects the variables onto a unit sphere and is related to global contrast normalization. The spatial sign of a vector w is w/norm(w).

The variables should be centered and scaled prior to the computations.

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 which is the columns that will be affected.

References

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.

Examples

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)
tidy(ss_obj, number = 3)

recipes

Preprocessing Tools to Create Design Matrices

v0.1.16

MIT + file LICENSE

Authors

Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]

Initial release