evaluate_gazepoint_nested_resampling: Evaluate nested grouped resampling with inner governed tuning

In gp3ml: Governance-First Predictive Modelling for 'Gazepoint' Research

Evaluate nested grouped resampling with inner governed tuning

Description

Evaluate nested grouped resampling with inner governed tuning

Usage

evaluate_gazepoint_nested_resampling(
  nested_folds,
  task,
  tuning_grid,
  selection_metric,
  direction,
  predictors = NULL,
  minimum_success_prop = 0.8,
  tie_breakers = NULL,
  selection_rationale = .gp3ml_nested_selection_rationale_default,
  seed = 1L,
  keep_models = FALSE,
  continue_on_error = TRUE
)

## S3 method for class 'gp3ml_nested_evaluation'
print(x, ...)

Arguments

nested_folds	A gp3ml_nested_folds object.
task	Governed task.
tuning_grid	Explicit tuning grid.
selection_metric	Explicit inner selection metric.
direction	Explicit selection direction.
predictors	Optional predictors.
minimum_success_prop	Minimum inner-fold success proportion.
tie_breakers	Optional secondary metrics.
selection_rationale	Human rationale recorded for each outer fold.
seed	Base deterministic seed.
keep_models	Whether outer fitted models are retained.
continue_on_error	Whether failed outer folds remain in the result.
x	An object returned by the corresponding gp3ml constructor, evaluator, summarizer, or validator.
...	Additional arguments passed to the print method.

Value

A gp3ml_nested_evaluation object retaining inner tuning results, selections, outer predictions, metrics, and failures.

gp3ml documentation built on Aug. 23, 2026, 5:11 p.m.