plot_modeltime_resamples: Interactive Resampling Accuracy Plots

View source: R/plot_modeltime_resamples.R

plot_modeltime_resamplesR Documentation

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.