Hi,
In the context of model selection, I am performing cross-validation using the function modeltime_fit_resamples()
available in the package modeltime.resample
using the following code:
resamples_tscv <- time_series_cv(
data = df_train,
date_var = date,
assess = "2 months",
initial = "6 years",
skip = "1 month",
cumulative = TRUE
)
resamples_fitted <- models_tbl %>%
modeltime_fit_resamples(
resamples = resamples_tscv,
control = control_resamples(verbose = TRUE)
)
resamples_fitted %>%
modeltime_resample_accuracy() %>%
table_modeltime_accuracy()
After fitting the best model on the whole training set, I would like to assess its accuracy for the 2-months ahead predictions on an independent test set. Basically, I am looking for a function similar to modeltime_fit_resamples()
where the model is kept constant and not fitted on each resample. Does it exist?
Thanks in advance for your help,
Kind Regards,
Alessandro