Combine multiple Modeltime Tables into a single Modeltime Table




Multiple Modeltime Tables (class mdl_time_tbl)


This function combines multiple Modeltime Tables.

  • The .model_id will automatically be renumbered to ensure each model has a unique ID.

  • Only the .model_id, .model, and .model_desc columns will be returned.

Re-Training Models on the Same Datasets

One issue can arise if your models are trained on different datasets. If your models have been trained on different datasets, you can run modeltime_refit() to train all models on the same data.

Re-Calibrating Models

If your data has been calibrated using modeltime_calibrate(), the .test and .calibration_data columns will be removed. To re-calibrate, simply run modeltime_calibrate() on the newly combined Modeltime Table.

See also


library(modeltime) library(tidymodels) library(tidyverse) library(timetk) library(lubridate) # Setup m750 <- m4_monthly %>% filter(id == "M750") splits <- time_series_split(m750, assess = "3 years", cumulative = TRUE)
#> Using date_var: date
model_fit_arima <- arima_reg() %>% set_engine("auto_arima") %>% fit(value ~ date, training(splits))
#> frequency = 12 observations per 1 year
model_fit_prophet <- prophet_reg() %>% set_engine("prophet") %>% fit(value ~ date, training(splits))
#> Disabling weekly seasonality. Run prophet with weekly.seasonality=TRUE to override this.
#> Disabling daily seasonality. Run prophet with daily.seasonality=TRUE to override this.
# Multiple Modeltime Tables model_tbl_1 <- modeltime_table(model_fit_arima) model_tbl_2 <- modeltime_table(model_fit_prophet) # Combine combine_modeltime_tables(model_tbl_1, model_tbl_2)
#> # Modeltime Table #> # A tibble: 2 × 3 #> .model_id .model .model_desc #> <int> <list> <chr> #> 1 1 <fit[+]> ARIMA(0,1,1)(0,1,1)[12] #> 2 2 <fit[+]> PROPHET