This generic is used to provide a description of an rtemis object in plain language.
Examples
species_lightrf <- train(iris, algorithm = "lightrf")
#> 2026-02-15 11:20:23
#> ▶
#> [train]
#> 2026-02-15 11:20:23
#> Training set: 150 cases x 4 features.
#> [summarize_supervised]
#> 2026-02-15 11:20:23
#> // Max workers: 7 => Algorithm: 7; Tuning: 1; Outer Resampling: 1
#> [get_n_workers]
#> 2026-02-15 11:20:23
#> Training LightRF Classification...
#> [train]
#> 2026-02-15 11:20:23
#> Checking data is ready for training...
#>
#> ✓
#> [check_supervised]
#>
#>
#> <Classification>
#> LightRF (LightGBM Random Forest)
#>
#> <Training Classification Metrics>
#> Predicted
#> Reference setosa versicolor virginica
#> setosa 50 0 0
#> versicolor 1 44 5
#> virginica 0 1 49
#>
#> Overall
#> Balanced_Accuracy 0.953
#> F1 0.953
#> Accuracy 0.953
#> setosa versicolor virginica
#> Sensitivity 1.000 0.880 0.980
#> Specificity 0.990 0.990 0.950
#> Balanced_Accuracy 0.995 0.935 0.965
#> PPV 0.980 0.978 0.907
#> NPV 1.000 0.943 0.990
#> F1 0.990 0.926 0.942
#>
#> 2026-02-15 11:20:24
#> ✓ Done in 1.26 seconds.
#> [train]
describe(species_lightrf)
#> LightGBM Random Forest was used for classification.
#> Balanced accuracy was 0.95 on the training set.