MachineShop (version 3.8.0)

recipe_roles: Set Recipe Roles

Description

Add to or replace the roles of variables in a preprocessing recipe.

Usage

role_binom(recipe, x, size)
role_case(recipe, group, stratum, weight, replace = FALSE)
role_pred(recipe, offset, replace = FALSE)
role_surv(recipe, time, event)

Value

An updated recipe object.

Arguments

recipe

existing recipe object.

x, size

number of counts and trials for the specification of a BinomialVariate outcome.

group

variable defining groupings of case observations, such as repeated measurements, to keep together during resampling [default: none].

stratum

variable to use in conducting stratified resample estimation of model performance.

weight

numeric variable of case weights for model fitting.

replace

logical indicating whether to replace existing roles.

offset

numeric variable to be added to a linear predictor, such as in a generalized linear model, with known coefficient 1 rather than an estimated coefficient.

time, event

numeric follow up time and 0-1 numeric or logical event indicator for specification of a Surv outcome. If the event indicator is omitted, all cases are assumed to have events.

See Also

recipe

Examples

library(survival)
library(recipes)

df <- within(veteran, {
  y <- Surv(time, status)
  remove(time, status)
})
rec <- recipe(y ~ ., data = df) %>%
  role_case(stratum = y)

(res <- resample(rec, model = CoxModel))
summary(res)