Refit one or more trained models to new dataSource:
This is a wrapper for
fit() that takes a
Modeltime Table and retrains each model on new data re-using the parameters
and preprocessing steps used during the training process.
modeltime_refit(object, data, ..., control = control_refit())
A Modeltime Table
tibblethat contains data to retrain the model(s) using.
Additional arguments to control refitting.
Ensemble Model Spec (
When making a meta-learner with
modeltime.ensemble::ensemble_model_spec(), used to pass
resamplesargument containing results from
Used to control verbosity and parallel processing. See
Refitting is an important step prior to forecasting time series models.
modeltime_refit() function makes it easy to recycle models,
retraining on new data.
Parameters are recycled during retraining using the following criteria:
Automated models (e.g. "auto arima") will have parameters recalculated.
Non-automated models (e.g. "arima") will have parameters preserved.
All preprocessing steps will be reused on the data
modeltime_refit() function is used to retrain models trained with
The XY format is not supported at this time.
library(tidyverse) library(lubridate) library(timetk) library(parsnip) library(rsample) library(modeltime) # Data m750 <- m4_monthly %>% filter(id == "M750") # Split Data 80/20 splits <- initial_time_split(m750, prop = 0.9) # --- MODELS --- model_fit_prophet <- prophet_reg() %>% set_engine(engine = "prophet") %>% fit(value ~ date, data = 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. # ---- MODELTIME TABLE ---- models_tbl <- modeltime_table( model_fit_prophet ) # ---- CALIBRATE ---- # - Calibrate on training data set calibration_tbl <- models_tbl %>% modeltime_calibrate(new_data = testing(splits)) # ---- REFIT ---- # - Refit on full data set refit_tbl <- calibration_tbl %>% modeltime_refit(m750) #> Disabling weekly seasonality. Run prophet with weekly.seasonality=TRUE to override this. #> Disabling daily seasonality. Run prophet with daily.seasonality=TRUE to override this.