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,