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Density Plot of Bias Corrections from SHAP values

Source: R/create_beta_correction_plot_functions.R
bias_density.Rd

Visualizes the distribution of SHAP corrections that are migrated to bias terms, showing both per-variable and total bias corrections.

NOTE This function signature documents the interface of functions created by create_bias_density.

Usage

bias_density(q = 0, type = "hist")

Arguments

q

Numeric value between 0 and 0.5 for quantile bounds. A higher number will trim more from the edges (useful if outliers are distorting your plot window) Default is 0 (i.e. no trimming)

type

Character string specifying plot type: "kde" for kernel density or "hist" for histogram. Default is "hist".

Value

A list with two ggplot objects:

  • bias_correction_var: Faceted plot showing bias correction density from each variable. Note that variables with no records contributing to bias correction are dropped from the plot.

  • bias_correction_total: Plot showing total corrected bias density.

See also

create_bias_density, explain_iblm

Examples

# This function is created inside explain_iblm() and is output as an item

df_list <- freMTPLmini |> split_into_train_validate_test(seed = 9000)

iblm_model <- train_iblm_xgb(
  df_list,
  response_var = "ClaimRate",
  family = "poisson"
)

explain_objects <- explain_iblm(iblm_model, df_list$test)

explain_objects$bias_density()
#> $bias_correction_var

#> 
#> $bias_correction_total

#> 


# This function must be created, and cannot be called directly from the package
try(
bias_density()
)
#> Error in bias_density() : 
#>   This function documents the interface only and cannot be called
#> directly. Instead, try one of the following
#> ℹ Use explain_iblm()$bias_density()
#> ℹ Call a function output from create_bias_density()