step_ratio
creates a specification of a recipe
step that will create one or more ratios out of numeric
variables.
step_ratio( recipe, ..., role = "predictor", trained = FALSE, denom = denom_vars(), naming = function(numer, denom) make.names(paste(numer, denom, sep = "_o_")), columns = NULL, skip = FALSE, id = rand_id("ratio") ) denom_vars(...) # S3 method for step_ratio tidy(x, ...)
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 in the numerator of the ratio.
When used with |
role | For terms created by this step, what analysis role should they be assigned?. By default, the function assumes that the newly created ratios created by the original variables will be used as predictors in a model. |
trained | A logical to indicate if the quantities for preprocessing have been estimated. |
denom | A call to |
naming | A function that defines the naming convention for new ratio columns. |
columns | The column names used in the ratios. This
argument is not populated until |
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. |
x | A |
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
(the
selectors or variables selected) and denom
.
library(recipes) library(modeldata) data(biomass) biomass$total <- apply(biomass[, 3:7], 1, sum) biomass_tr <- biomass[biomass$dataset == "Training",] biomass_te <- biomass[biomass$dataset == "Testing",] rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur + total, data = biomass_tr) ratio_recipe <- rec %>% # all predictors over total step_ratio(all_predictors(), denom = denom_vars(total)) %>% # get rid of the original predictors step_rm(all_predictors(), -ends_with("total")) ratio_recipe <- prep(ratio_recipe, training = biomass_tr) ratio_data <- bake(ratio_recipe, biomass_te) ratio_data#> # A tibble: 80 x 7 #> total HHV carbon_o_total hydrogen_o_total oxygen_o_total nitrogen_o_total #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 99.7 18.3 0.465 0.0568 0.473 0.00301 #> 2 100 17.6 0.432 0.055 0.481 0.0285 #> 3 100 17.2 0.427 0.055 0.491 0.024 #> 4 92.1 18.9 0.504 0.0662 0.405 0.0195 #> 5 98.0 20.5 0.497 0.0645 0.436 0.00204 #> 6 92.4 18.5 0.479 0.0595 0.451 0.00758 #> 7 100 15.1 0.389 0.0523 0.541 0.0119 #> 8 81.7 16.2 0.515 0.0570 0.414 0.0116 #> 9 69.7 11.1 0.419 0.0631 0.446 0.00201 #> 10 60.9 10.8 0.456 0.0619 0.389 0.0760 #> # … with 70 more rows, and 1 more variable: sulfur_o_total <dbl>