Describe rtemis object

This generic is used to provide a description of an rtemis object in plain language.

Usage

describe(x, ...)

Arguments

x

Supervised or SupervisedRes object or list of such objects.

...

Not used.

Value

A character string describing the object.

Author

EDG

Examples

species_lightrf <- train(iris, algorithm = "lightrf")
#> 2026-02-22 18:59:16 
#> ▶
#>  [train]
#> 2026-02-22 18:59:16 
#> Training set: 150 cases x 4 features.
#>  [summarize_supervised]
#> 2026-02-22 18:59:16 
#> // Max workers: 7 => Algorithm: 7; Tuning: 1; Outer Resampling: 1
#>  [get_n_workers]
#> 2026-02-22 18:59:16 
#> Training LightRF Classification...
#>  [train]
#> 2026-02-22 18:59:16 
#> Checking data is ready for training...
#>  
#> ✓ 
#> [check_supervised]
#> 
#> 2026-02-22 18:59:16 
#> Converting 1 factor to integer...
#>  [preprocess]
#> 2026-02-22 18:59:16 
#> Preprocessing done.
#>  [preprocess]
#> 
#> <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    
#> 
#> 2026-02-22 18:59:18 
#> ✓ Done in 1.46 seconds.
#>  [train]
describe(species_lightrf)
#> LightGBM Random Forest was used for classification.
#> Balanced accuracy was 0.95 on the training set.