plot.light_importance: Visualize Variable Importance

In mayer79/flashlight: Shed Light on Black Box Machine Learning Models

Visualize Variable Importance

Description

Visualization of an object of class "light_importance" via ggplot2::geom_bar(). If available, standard errors are added by ggplot2::geom_errorbar(). The object returned is of class "ggplot" and can be further customized.

Usage

## S3 method for class 'light_importance'
plot(
  x,
  top_m = Inf,
  swap_dim = FALSE,
  facet_scales = "fixed",
  rotate_x = FALSE,
  error_bars = TRUE,
  ...
)

Arguments

x	An object of class "light_importance".
top_m	Maximum number of important variables to be returned.
swap_dim	If multiflashlight and one "by" variable or single flashlight with two "by" variables, swap the role of dodge/fill variable and facet variable. If multiflashlight or one "by" variable, use facets instead of colors.
facet_scales	Scales argument passed to ggplot2::facet_wrap().
rotate_x	Should x axis labels be rotated by 45 degrees?
error_bars	Should error bars be added? Defaults to TRUE. Only available if light_importance() was run with multiple permutations by setting m_repetitions > 1.
...	Further arguments passed to ggplot2::geom_bar().

Details

The plot is organized as a bar plot with variable names as x-aesthetic. Up to two additional dimensions (multiflashlight and one "by" variable or single flashlight with two "by" variables) can be visualized by facetting and dodge/fill. Set swap_dim = FALSE to revert the role of these two dimensions. One single additional dimension is visualized by a facet wrap, or - if swap_dim = FALSE - by dodge/fill.

Value

An object of class "ggplot".

See Also

light_importance()

mayer79/flashlight documentation built on Feb. 13, 2024, 1:09 p.m.