This function is used to quickly create a workflowsets object.
Usage
ts_wfs_ets_reg(
.model_type = "all_engines",
.recipe_list,
.seasonal_period = "auto",
.error = "auto",
.trend = "auto",
.season = "auto",
.damping = "auto",
.smooth_level = 0.1,
.smooth_trend = 0.1,
.smooth_seasonal = 0.1
)Arguments
- .model_type
This is where you will set your engine. It uses
modeltime::exp_smoothing()under the hood and can take one of the following:"ets"
"croston"
"theta"
"smooth_es"
"all_engines" - This will make a model spec for all available engines.
- .recipe_list
You must supply a list of recipes. list(rec_1, rec_2, ...)
- .seasonal_period
A seasonal frequency. Uses "auto" by default. A character phrase of "auto" or time-based phrase of "2 weeks" can be used if a date or date-time variable is provided. See Fit Details below.
- .error
The form of the error term: "auto", "additive", or "multiplicative". If the error is multiplicative, the data must be non-negative.
- .trend
The form of the trend term: "auto", "additive", "multiplicative" or0 "none".
- .season
The form of the seasonal term: "auto", "additive", "multiplicative" or "none".
- .damping
Apply damping to a trend: "auto", "damped", or "none".
- .smooth_level
This is often called the "alpha" parameter used as the base level smoothing factor for exponential smoothing models.
- .smooth_trend
This is often called the "beta" parameter used as the trend smoothing factor for exponential smoothing models.
- .smooth_seasonal
This is often called the "gamma" parameter used as the seasonal smoothing factor for exponential smoothing models.
Details
This function expects to take in the recipes that you want to use in the modeling process. This is an automated workflow process. There are sensible defaults set for the model specification, but if you choose you can set them yourself if you have a good understanding of what they should be. The mode is set to "regression".
This uses the following engines:
modeltime::exp_smoothing() exp_smoothing() is a way to generate a specification
of an Exponential Smoothing model before fitting and allows the model to be
created using different packages. Currently the only package is forecast.
Several algorithms are implemented:
"ets"
"croston"
"theta"
"smooth_es
See also
https://workflowsets.tidymodels.org/
https://business-science.github.io/modeltime/reference/exp_smoothing.html
Other Auto Workflowsets:
ts_wfs_arima_boost(),
ts_wfs_auto_arima(),
ts_wfs_lin_reg(),
ts_wfs_mars(),
ts_wfs_nnetar_reg(),
ts_wfs_prophet_reg(),
ts_wfs_svm_poly(),
ts_wfs_svm_rbf(),
ts_wfs_xgboost()
Examples
suppressPackageStartupMessages(library(modeltime))
suppressPackageStartupMessages(library(timetk))
suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(rsample))
data <- AirPassengers %>%
ts_to_tbl() %>%
select(-index)
splits <- time_series_split(
data
, date_col
, assess = 12
, skip = 3
, cumulative = TRUE
)
rec_objs <- ts_auto_recipe(
.data = training(splits)
, .date_col = date_col
, .pred_col = value
)
wf_sets <- ts_wfs_ets_reg("all_engines", rec_objs)
wf_sets
#> # A workflow set/tibble: 16 × 4
#> wflow_id info option result
#> <chr> <list> <list> <list>
#> 1 rec_base_exp_smoothing_1 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 2 rec_base_exp_smoothing_2 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 3 rec_base_exp_smoothing_3 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 4 rec_base_exp_smoothing_4 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 5 rec_date_exp_smoothing_1 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 6 rec_date_exp_smoothing_2 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 7 rec_date_exp_smoothing_3 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 8 rec_date_exp_smoothing_4 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 9 rec_date_fourier_exp_smoothing_1 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 10 rec_date_fourier_exp_smoothing_2 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 11 rec_date_fourier_exp_smoothing_3 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 12 rec_date_fourier_exp_smoothing_4 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 13 rec_date_fourier_nzv_exp_smoothing_1 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 14 rec_date_fourier_nzv_exp_smoothing_2 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 15 rec_date_fourier_nzv_exp_smoothing_3 <tibble [1 × 4]> <opts[0]> <list [0]>
#> 16 rec_date_fourier_nzv_exp_smoothing_4 <tibble [1 × 4]> <opts[0]> <list [0]>