plot_tile_int_Shapley: Tileplot of Shapley values for interval-valued data.

In AIDA: Analysis of Interval DAta

Tileplot of Shapley values for interval-valued data.

Description

Tileplot of Shapley values for interval-valued data.

Usage

plot_tile_int_Shapley(
  shapley,
  outliers = NULL,
  rotate_x = TRUE,
  abbrev.var = FALSE,
  abbrev.obs = FALSE,
  sort.var = FALSE,
  sort.obs = FALSE,
  show_values = FALSE
)

Arguments

shapley	A n \times p matrix containing the Shapley values of n observations and p variables.
outliers	A list containing the outliers' names as returned by int_outliers. If outliers is not NULL (default), only the outliers are highlighted in the plot.
rotate_x	Logical. If TRUE (default), the x-axis labels are rotated.
abbrev.var	Integer. If abbrev.var > 0, column names are abbreviated using abbreviate with minlenght = abrev.var.
abbrev.obs	Integer. If abbrev.obs > 0, row names are abbreviated using abbreviate with minlenght = abrev.obs.
sort.var	Logical. If TRUE, variables are sorted according to the distance.
sort.obs	Logical. If TRUE, observations are sorted according to their squared Interval-Mahalanobis distance.
show_values	Logical. If TRUE, the Shapley values are displayed in each tile.

Value

Returns a tileplot that displays the Shapley values (int_Shapley) for each observation and variable. Optionally, only the outliers are highlighted in the plot.

References

Adapted from package ShapleyOutlier (https://CRAN.R-project.org/package=ShapleyOutlier).

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)

plot_tile_int_Shapley(credit_card_shapley, 
                     outliers = credit_card_outliers, 
                     sort.var = TRUE, 
                     sort.obs = TRUE)

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