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The predictions sdt_fit() made on the test half of its own split, with the truth alongside. This is what the metrics were computed from.

Usage

sdt_predictions(model)

Arguments

model

An sdt_model from sdt_fit().

Value

A tibble::tibble() with .pred_class, the per-class probability columns, and truth.

Examples

# See ?sdt_fit for a runnable example.
sdt_metric_set
#> function () 
#> {
#>     .require_pkgs("yardstick")
#>     yardstick::metric_set(yardstick::roc_auc, yardstick::accuracy, 
#>         yardstick::kap, yardstick::f_meas)
#> }
#> <bytecode: 0x588cde4903d0>
#> <environment: namespace:sandtablR>