modeltime_resample_accuracy {modeltime.resample} | R Documentation |
Calculate Accuracy Metrics from Modeltime Resamples
Description
This is a wrapper for yardstick
that simplifies time
series regression accuracy metric calculations from
a Modeltime Table that has been resampled and fitted using
modeltime_fit_resamples()
.
Usage
modeltime_resample_accuracy(
object,
summary_fns = mean,
metric_set = default_forecast_accuracy_metric_set(),
...
)
Arguments
object |
a Modeltime Table with a column '.resample_results' (the output of |
summary_fns |
One or more functions to analyze resamples. The default is
|
metric_set |
A |
... |
Additional arguments passed to the function calls in |
Details
#' Default Accuracy Metrics
The following accuracy metrics are included by default via modeltime::default_forecast_accuracy_metric_set()
:
MAE - Mean absolute error,
yardstick::mae()
MAPE - Mean absolute percentage error,
yardstick::mape()
MASE - Mean absolute scaled error,
yardstick::mase()
SMAPE - Symmetric mean absolute percentage error,
yardstick::smape()
RMSE - Root mean squared error,
yardstick::rmse()
RSQ - R-squared,
yardstick::rsq()
Summary Functions
By default, modeltime_resample_accuracy()
returns
the average accuracy metrics for each resample prediction.
The user can change this default behavior using summary_fns
.
Simply pass one or more Summary Functions. Internally, the functions are passed to
dplyr::across(.fns)
, which applies the summary functions.
Returning Unsummarized Results
You can pass summary_fns = NULL
to return unsummarized results by .resample_id
.
Professional Tables (Interactive & Static)
Use modeltime::table_modeltime_accuracy()
to format the results for reporting in
reactable
(interactive) or gt
(static) formats, which are perfect for
Shiny Apps (interactive) and PDF Reports (static).
Examples
library(modeltime)
# Mean (Default)
m750_training_resamples_fitted %>%
modeltime_resample_accuracy() %>%
table_modeltime_accuracy(.interactive = FALSE)
# Mean and Standard Deviation
m750_training_resamples_fitted %>%
modeltime_resample_accuracy(
summary_fns = list(mean = mean, sd = sd)
) %>%
table_modeltime_accuracy(.interactive = FALSE)
# When summary_fns = NULL, returns the unsummarized resample results
m750_training_resamples_fitted %>%
modeltime_resample_accuracy(
summary_fns = NULL
)