plot_modeltime_resamples: Interactive Resampling Accuracy Plots

In modeltime.resample: Resampling Tools for Time Series Forecasting

Interactive Resampling Accuracy Plots

Description

A convenient plotting function for visualizing resampling accuracy by resample set for each model in a Modeltime Table.

Usage

plot_modeltime_resamples(
  .data,
  .metric_set = default_forecast_accuracy_metric_set(),
  .summary_fn = mean,
  ...,
  .facet_ncol = NULL,
  .facet_scales = "free_x",
  .point_show = TRUE,
  .point_size = 1,
  .point_shape = 16,
  .point_alpha = 1,
  .summary_line_show = TRUE,
  .summary_line_size = 0.5,
  .summary_line_type = 1,
  .summary_line_alpha = 1,
  .x_intercept = NULL,
  .x_intercept_color = "red",
  .x_intercept_size = 0.5,
  .legend_show = TRUE,
  .legend_max_width = 40,
  .title = "Resample Accuracy Plot",
  .x_lab = "",
  .y_lab = "",
  .color_lab = "Legend",
  .interactive = TRUE
)

Arguments

.data	A modeltime table that includes a column .resample_results containing the resample results. See modeltime_fit_resamples() for more information.
.metric_set	A yardstick::metric_set() that is used to summarize one or more forecast accuracy (regression) metrics.
.summary_fn	A single summary function that is applied to aggregate the metrics across resample sets. Default: mean.
...	Additional arguments passed to the .summary_fn.
.facet_ncol	Default: NULL. The number of facet columns.
.facet_scales	Default: free_x.
.point_show	Whether or not to show the individual points for each combination of models and metrics. Default: TRUE.
.point_size	Controls the point size. Default: 1.
.point_shape	Controls the point shape. Default: 16.
.point_alpha	Controls the opacity of the points. Default: 1 (full opacity).
.summary_line_show	Whether or not to show the summary lines. Default: TRUE.
.summary_line_size	Controls the summary line size. Default: 0.5.
.summary_line_type	Controls the summary line type. Default: 1.
.summary_line_alpha	Controls the summary line opacity. Default: 1 (full opacity).
.x_intercept	Numeric. Adds an x-intercept at a location (e.g. 0). Default: NULL.
.x_intercept_color	Controls the x-intercept color. Default: "red".
.x_intercept_size	Controls the x-intercept size. Default: 0.5.
.legend_show	Logical. Whether or not to show the legend. Can save space with long model descriptions.
.legend_max_width	Numeric. The width of truncation to apply to the legend text.
.title	Title for the plot
.x_lab	X-axis label for the plot
.y_lab	Y-axis label for the plot
.color_lab	Legend label if a color_var is used.
.interactive	Returns either a static (ggplot2) visualization or an interactive (plotly) visualization

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 Function

Users can supply a single summary function (e.g. mean) to summarize the resample metrics by each model.

Examples

m750_training_resamples_fitted %>%
    plot_modeltime_resamples(
        .interactive = FALSE
    )

modeltime.resample documentation built on April 14, 2023, 12:31 a.m.