Add a Model into a Modeltime Table

Add a Model into a Modeltime Table

Usage

add_modeltime_model(object, model, location = "bottom")

Arguments

object

Multiple Modeltime Tables (class mdl_time_tbl)

model

A model of class model_fit or a fitted workflow object

location

Where to add the model. Either "top" or "bottom". Default: "bottom".

See also

• combine_modeltime_tables(): Combine 2 or more Modeltime Tables together

• add_modeltime_model(): Adds a new row with a new model to a Modeltime Table

• drop_modeltime_model(): Drop one or more models from a Modeltime Table

• update_modeltime_description(): Updates a description for a model inside a Modeltime Table

• update_modeltime_model(): Updates a model inside a Modeltime Table

• pull_modeltime_model(): Extracts a model from a Modeltime Table

Examples

# \donttest{
library(tidymodels)
#> ── Attaching packages ────────────────────────────────────── tidymodels 1.3.0 ──
#> ✔ broom        1.0.9     ✔ tibble       3.3.0
#> ✔ dials        1.4.1     ✔ tidyr        1.3.1
#> ✔ ggplot2      3.5.2     ✔ tune         1.3.0
#> ✔ infer        1.0.9     ✔ workflows    1.3.0
#> ✔ modeldata    1.5.1     ✔ workflowsets 1.1.1
#> ✔ purrr        1.1.0     ✔ yardstick    1.3.2
#> ✔ recipes      1.3.1     
#> ── Conflicts ───────────────────────────────────────── tidymodels_conflicts() ──
#> ✖ yardstick::accuracy() masks smooth::accuracy(), greybox::accuracy()
#> ✖ purrr::discard()      masks scales::discard()
#> ✖ dplyr::filter()       masks stats::filter()
#> ✖ dplyr::lag()          masks stats::lag()
#> ✖ smooth::pls()         masks parsnip::pls()
#> ✖ tidyr::spread()       masks greybox::spread()
#> ✖ recipes::step()       masks stats::step()

model_fit_ets <- exp_smoothing() %>%
    set_engine("ets") %>%
    fit(value ~ date, training(m750_splits))
#> frequency = 12 observations per 1 year

m750_models %>%
    add_modeltime_model(model_fit_ets)
#> # Modeltime Table
#> # A tibble: 4 × 3
#>   .model_id .model     .model_desc            
#>       <int> <list>     <chr>                  
#> 1         1 <workflow> ARIMA(0,1,1)(0,1,1)[12]
#> 2         2 <workflow> PROPHET                
#> 3         3 <workflow> GLMNET                 
#> 4         4 <fit[+]>   ETS(A,A,A)             
# }