fix typos

materials/exercises/04-Ensembling.Rmd

@@ -85,7 +85,7 @@ Compare the metrics of the random forest to your two single tree models (vanilla
 
 # Your Turn 6
 
-Challenge: Make 4 more random forest model specs, each using 4, 8, 12, and 20 variables at each split. Which value maximizes the area under the ROC curve?
+Challenge: Make 4 more random forest model specs, each using 4, 8, 12, and 19 variables at each split. Which value maximizes the area under the ROC curve?
 
 *Hint: you'll need https://tidymodels.github.io/parsnip/reference/rand_forest.html*
 

materials/exercises/06-case-study/random-forest.R

@@ -24,7 +24,7 @@ val_set <- validation_split(hotel_other,
 # specify un-tuned parsnip model------------------------------------------------
 # EDIT ME TO TUNE!==============================================================
 rf_spec <- 
-  rand_forest(trees = 1000) %>% 
+  rand_forest(mtry = tune(), min_n = tune()) %>% 
   set_engine("ranger") %>% 
   set_mode("classification")
 
@@ -41,11 +41,13 @@ rf_workflow <-
   add_model(rf_spec) %>% 
   add_recipe(rf_recipe)
 
+rf_grid <- expand_grid(mtry = c(1, 5, 10), min_n = c(10, 20, 30))
 # train/tune--------------------------------------------------------------------
 set.seed(345)
 # EDIT ME TO TUNE!==============================================================
 rf_results <- 
   rf_workflow %>% 
-  fit_resamples(resamples = val_set,
-                control = control_resamples(save_pred = TRUE),
-                metrics = metric_set(roc_auc))
+  tune_grid(resamples = val_set,
+            grid = rf_grid,
+            control = control_grid(save_pred = TRUE),
+            metrics = metric_set(roc_auc))