Explain a fitted mass-casualty model

Wraps a fitted sdt_fit() model in a DALEX explainer, so permutation importance, dependence profiles and per-casualty attributions all work off one object.

Usage

sdt_explain(model, data = NULL, y = NULL)

Arguments

model

An sdt_model from sdt_fit().

data

Data to explain on. Defaults to the held-out half of the model's own split, which is the right choice: explaining a model on the rows it was fitted to flatters it.

y

Optional true outcome vector; taken from data when omitted.

Value

A DALEX explainer.

See also

sdt_importance(), sdt_profile(), sdt_shap().

Examples

# See ?sdt_importance for a runnable example.
sdt_engines()
#> # A tibble: 9 × 4
#>   engine      package class_box installed
#>   <chr>       <chr>   <chr>     <lgl>    
#> 1 tree        rpart   glass     TRUE     
#> 2 multinom    nnet    glass     TRUE     
#> 3 glmnet      glmnet  glass     TRUE     
#> 4 mars        earth   grey      TRUE     
#> 5 xgboost     xgboost grey      TRUE     
#> 6 ranger      ranger  black     TRUE     
#> 7 svm_rbf     kernlab black     TRUE     
#> 8 mlp         nnet    black     TRUE     
#> 9 transformer keras3  closed    TRUE