ts_model_rank_tbl {healthyR.ts} | R Documentation |
Model Rank
Description
This takes in a calibration tibble and computes the ranks of the models inside of it.
Usage
ts_model_rank_tbl(.calibration_tbl)
Arguments
.calibration_tbl |
A calibrated modeltime table. |
Details
This takes in a calibration tibble and computes the ranks of the models inside
of it. It computes for now only the default yardstick
metrics from modeltime
These are the following using the dplyr
min_rank()
function with desc
use
on rsq
:
"rmse"
"mae"
"mape"
"smape"
"rsq"
Value
A tibble with models ranked by metric performance order
Author(s)
Steven P. Sanderson II, MPH
See Also
Other Utility:
auto_stationarize()
,
calibrate_and_plot()
,
internal_ts_backward_event_tbl()
,
internal_ts_both_event_tbl()
,
internal_ts_forward_event_tbl()
,
model_extraction_helper()
,
ts_get_date_columns()
,
ts_info_tbl()
,
ts_is_date_class()
,
ts_lag_correlation()
,
ts_model_auto_tune()
,
ts_model_compare()
,
ts_model_spec_tune_template()
,
ts_qq_plot()
,
ts_scedacity_scatter_plot()
,
ts_to_tbl()
,
util_difflog_ts()
,
util_doublediff_ts()
,
util_doubledifflog_ts()
,
util_log_ts()
,
util_singlediff_ts()
Examples
# NOT RUN
## Not run:
suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(timetk))
suppressPackageStartupMessages(library(modeltime))
suppressPackageStartupMessages(library(rsample))
suppressPackageStartupMessages(library(workflows))
suppressPackageStartupMessages(library(parsnip))
suppressPackageStartupMessages(library(recipes))
data_tbl <- ts_to_tbl(AirPassengers) %>%
select(-index)
splits <- time_series_split(
data_tbl,
date_var = date_col,
assess = "12 months",
cumulative = TRUE
)
rec_obj <- recipe(value ~ ., training(splits))
model_spec_arima <- arima_reg() %>%
set_engine(engine = "auto_arima")
model_spec_mars <- mars(mode = "regression") %>%
set_engine("earth")
wflw_fit_arima <- workflow() %>%
add_recipe(rec_obj) %>%
add_model(model_spec_arima) %>%
fit(training(splits))
wflw_fit_mars <- workflow() %>%
add_recipe(rec_obj) %>%
add_model(model_spec_mars) %>%
fit(training(splits))
model_tbl <- modeltime_table(wflw_fit_arima, wflw_fit_mars)
calibration_tbl <- model_tbl %>%
modeltime_calibrate(new_data = testing(splits))
ts_model_rank_tbl(calibration_tbl)
## End(Not run)