Generate SHAP (SHapley Additive exPlanations) Plots for Multiple Models and Responses

This function generates SHAP (SHapley Additive exPlanations) plots for multiple models and responses.

Usage

MrShapely(
  yhats,
  MultRespVars = Resp,
  taxa = NULL,
  kind = "beeswarm",
  max_display = 15L,
  color_var = NULL,
  getFeaturePlot = TRUE,
  getDependencyPlot = TRUE,
  get2DDependencyPlot = TRUE,
  num_cores = 2,
  class_selection = NULL
)

Arguments

yhats: A list of model prediction objects. Each object should contain a model, data, and class information.
MultRespVars: A data frame containing response variables for the prediction.
taxa: An optional vector specifying which responses to include based on their indices.
kind: A character string specifying the type of plots (e.g., "beeswarm" for feature effect plot, "bar" for variable importance plot, or "both").
max_display: An integer specifying the maximum number of features to display.
color_var: A variable to use for coloring in the dependency plots.
getFeaturePlot: A logical indicating whether to generate feature effect plots.
getDependencyPlot: A logical indicating whether to generate dependency plots.
num_cores: An integer specifying the number of CPU cores to use for parallel processing.
class_selection: An optional vector specifying which classes to include in the plots.
x_features: A character vector specifying the features to consider in the plots.
y_features: A character vector specifying the response features for interaction plots.
interactions: A logical indicating whether to create interaction effect plots.
getInteractionPlot: A logical indicating whether to generate interaction plots.

Value

A ggplot object containing SHAP plots for the specified responses and features. Note that this function may not work for some algorithm classe (e.g., neural nets)

Examples

# Example usage:
MrShapely(yhats, MultRespVars = Resp)
#> Error in plan(future::multisession, workers = num_cores): could not find function "plan"