plot_beeswarm_int_Shapley: Beeswarm plot of Shapley values for interval-valued data.

In AIDA: Analysis of Interval DAta

Beeswarm plot of Shapley values for interval-valued data.

Description

Beeswarm plot of Shapley values for interval-valued data.

Usage

plot_beeswarm_int_Shapley(
  shapley,
  color_class,
  color_label = NULL,
  palette = NULL,
  rotate_x = TRUE,
  shape_class = NULL,
  shape_label = NULL,
  ggplotly = FALSE,
  label_obs = NULL,
  y_limits = NULL
)

Arguments

shapley	A n \times p matrix containing the Shapley values of n observations and p variables.
color_class	A vector indicating the color class of each observation. If NULL (default), all points have the same color.
color_label	Character. Label for the color class. If NULL (default), no legend for the color class is shown.
palette	A vector with colors for each color class. Default is NULL.
rotate_x	Logical. If TRUE (default), the x-axis labels are rotated.
shape_class	A vector indicating the shape class of each observation. If NULL (default), all points have the same shape.
shape_label	Character. Label for the shape class. If NULL (default), no legend for the shape class is shown.
ggplotly	Logical. If TRUE (default), the plot is converted to an interactive plotly object.
label_obs	A vector with the names of the observations to be labeled in the plot when ggplotly = FALSE. Default is NULL.
y_limits	A numeric vector of length 2 specifying the limits for the y-axis. Default is NULL, so the limits are determined automatically.

Value

Returns a beeswarm plot that displays the Shapley values (int_Shapley) for each observation and feature.

Examples

# Create intData object
data(creditcard)
credit_card_int <- creditcard$intData

# Estimate the mean and covariance matrix
credit_card_IMCD <- IMCD(credit_card_int, 
                         m = floor(nrow(credit_card_int)*0.75), 
                         cutoff = "farness", 
                         cutoff_lvl = 0.9)

# Detect outliers using farness cutoff
credit_card_outliers <- int_outliers(credit_card_IMCD$robust_dist, 
                                     cutoff = "farness", 
                                     cutoff_lvl = 0.9)

# Compute Shapley values
credit_card_shapley <- int_Shapley(credit_card_int, 
                                   mean_c = credit_card_IMCD$mean_IMCD_c,
                                   mean_r = credit_card_IMCD$mean_IMCD_r, 
                                   cov = credit_card_IMCD$cov_IMCD)

# Beeswarm plot of Shapley values colored by outlier status
plot_beeswarm_int_Shapley(credit_card_shapley, 
                     color_class = credit_card_outliers$is_outlier, 
                     palette = c("gray50", "darkred"), 
                     color_label = "Outlier Status")

AIDA documentation built on Nov. 4, 2026, 9:06 a.m.