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plug_split
library(tidymodels) # for the rsample package, along with the rest of tidymodels #> ── Attaching packages ────────────────────────────────────── tidymodels 0.1.0 ── #> ✔ broom 0.5.6 ✔ recipes 0.1.12 #> ✔ dials 0.0.7 ✔ rsample 0.0.7 #> ✔ dplyr 1.0.0 ✔ tibble 3.0.1 #> ✔ ggplot2 3.3.2 ✔ tune 0.1.0 #> ✔ infer 0.5.1 ✔ workflows 0.1.1 #> ✔ parsnip 0.1.1 ✔ yardstick 0.0.6 #> ✔ purrr 0.3.4 #> ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ── #> ✖ purrr::discard() masks scales::discard() #> ✖ dplyr::filter() masks stats::filter() #> ✖ dplyr::lag() masks stats::lag() #> ✖ recipes::step() masks stats::step() library(tidyflow) #> #> Attaching package: 'tidyflow' #> The following object is masked from 'package:tune': #> #> parameters #> The following object is masked from 'package:dials': #> #> parameters library(modeldata) # for the cells data data(cells, package = "modeldata") rf_mod <- rand_forest(trees = 1000) %>% set_engine("ranger") %>% set_mode("classification") rf_fit <- cells %>% tidyflow(seed = 123) %>% plug_split(initial_split, strata = class) %>% plug_formula(class ~ .) %>% plug_model(rf_mod) %>% fit() #> Error: This tidyselect interface doesn't support predicates yet. #> ℹ Contact the package author and suggest using `eval_select()`.
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