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()`.
