Update: Turns out, wrong input-format for stats::predict() leads to this missleading error message- because stats is 'guessing' to forecast an ets.
model_spec <-
boost_tree() %>%
set_engine("xgboost") %>%
set_mode("classification")
myModel<- workflow() %>%
add_model(model_spec) %>%
add_recipe(shelter_rec) %>%
parsnip::fit(df_train)
# https://parsnip.tidymodels.org/reference/predict.model_fit.html
testPred<-stats::predict(myModel,new_data=df_test)
View(testPred)
before I used stopping_fit as input for stats::predict()...
stopping_fit <- early_stop_wf %>%
finalize_workflow(select_best(stopping_rs, "accuracy")) %>%
last_fit(shelter_split)
whereas stopping_fit could be no real fit ;-).