nestcv.explain: Generate SHAP values from nestedcv models using shapr

In nestedcv: Nested Cross-Validation with 'glmnet' and 'caret'

Generate SHAP values from nestedcv models using shapr

Description

Convenience wrapper around shapr::explain() that works with nestedcv fitted models. Returns the shapr object directly, compatible with plot_shap_bar(), plot_shap_beeswarm(), and shapr's own print()/ plot() methods.

Usage

nestcv.explain(
  model,
  predict_model,
  x_explain = x_train,
  x_train = NULL,
  approach = "independence",
  phi0 = NULL,
  ...
)

Arguments

model	A nestcv.glmnet, nestcv.train, or other nestedcv model object.
predict_model	Prediction wrapper function with signature ⁠function(model, newdata)⁠ returning a numeric vector of predictions. Use pred_nestcv_glmnet(), pred_train(), pred_nestcv_glmnet_class(), pred_train_class(), or pred_SuperLearner() as appropriate.
x_explain	A matrix or data frame of feature values to compute SHAP values for. Defaults to x_train.
x_train	A matrix or data frame of feature values used as the background training data. Defaults to the original training data from model, which is stored as model$xsub[, model$final_vars] for fitted nestcv.glmnet/nestcv.train). Or users can supply their own training data.
approach	Character string specifying the shapr estimation approach. Defaults to "independence", which is the original method by Lundberg and is faster than other methods. The makers of shapr recommend "gaussian" for multivariate gaussian data or "empirical" as the main regression methods, i.e. if all x is numeric. For other approaches, see shapr::explain().
phi0	Numeric scalar; the baseline (null) prediction (i.e. the expected model output when no features are known). Defaults to NULL, in which case it is automatically computed as mean(model$y) or mean(predict_model(model, x_explain)) on supplied data for classification. For regression this equals mean(y_train); for classification it equals the mean predicted probability. Override this argument if you want to use a different reference value, e.g. computed on a held-out set.
...	Additional arguments passed to shapr::explain(), e.g. verbose.

Value

the shapr object returned by shapr::explain(). Pass it directly to plot_shap_bar() or plot_shap_beeswarm(), or use shapr's own print()/plot() methods on it.

nestedcv documentation built on July 14, 2026, 9:07 a.m.