I am trying to use tidymodels to run time series cross validation and have been following the Tidy Modeling with R chapters (10 Resampling for Evaluating Performance | Tidy Modeling with R).
When I run the following code, I get "Warning message: More than one set of outcomes were used when tuning. This should never happen. Review how the outcome is specified in your model."
The resamples$.metrics and resamples$.predictions are empty except for the first [[1]].
Any help is appreciated thank you!
library(tidyverse)
library(tidymodels)
df <- data.frame(
year_month = seq(as.Date("2020-01-01"), as.Date("2024-03-01"), "month"),
value = sample(1:100, length(seq(as.Date("2020-01-01"), as.Date("2024-03-01"), "month")))
)
splits <- sliding_window(df, lookback = Inf, skip=23, assess_start = 1, assess_stop = 1, complete = T)
model_spec <- arima_reg() %>%
set_engine("auto_arima")
resamples <- fit_resamples(
object = model_spec,
preprocessor = recipe(value ~ year_month, splits$splits[[1]]),
resamples = splits,
control = control_resamples(save_pred = TRUE)
)
collect_metrics(resamples)
resamples %>%
select(id, .predictions) %>%
unnest(.predictions)
