mlr3tuning (version 0.9.0)

extract_inner_tuning_results: Extract Inner Tuning Results

Description

Extract inner tuning results of nested resampling. Implemented for mlr3::ResampleResult and mlr3::BenchmarkResult. The function iterates over the AutoTuner objects and binds the tuning results to a data.table::data.table(). AutoTuner must be initialized with store_tuning_instance = TRUE and resample() or benchmark() must be called with store_models = TRUE.

Usage

extract_inner_tuning_results(x)

Arguments

x

(mlr3::ResampleResult | mlr3::BenchmarkResult).

Value

data.table::data.table().

Data structure

The returned data table has the following columns:

• experiment (integer(1)) Index, giving the according row number in the original benchmark grid.

• iteration (integer(1)) Iteration of the outer resampling.

• One column for each hyperparameter of the search spaces.

• One column for each performance measure.

• learner_param_vals (list()) Hyperparameter values used by the learner. Includes fixed and proposed hyperparameter values.

• x_domain (list()) List of transformed hyperparameter values.

• task_id (character(1)).

• learner_id (character(1)).

• resampling_id (character(1)).

Examples

# NOT RUN {
learner = lrn("classif.rpart", cp = to_tune(1e-04, 1e-1, logscale = TRUE))

at = auto_tuner(
  method = "grid_search",
  learner = learner,
  resampling = rsmp ("holdout"),
  measure = msr("classif.ce"),
  term_evals = 4)

resampling_outer = rsmp("cv", folds = 2)
rr = resample(tsk("iris"), at, resampling_outer, store_models = TRUE)

extract_inner_tuning_results(rr)
# }