Related Issues (20)
- find_feature_importance fails for multiclass data HOT 6
- Warning message about '%dorng%' vs '%dopar%' when run in parallel HOT 2
- Report p-values for permutation importance
- classification of new (and outcome unknown) samples HOT 1
- use which run_ml() output to plot ROC curve? HOT 2
- Impute missing values after the train/test split
- Refactor `select_apply()`
- Use hyperparams from `rf` for `parRF`
- meta-analysis using mikropml?
- NaN as character causes some problems HOT 3
- Extracting weights from 100 iterations and from random random forset model HOT 1
- Report confidence interval for permutation feature importance
- Create function to bootstrap the test set to get a confidence interval for performance
- Switch from {future.apply} to {furrr} where possible HOT 1
- roxygen2 docs: switch `@noRd` to `@keywords internal` for all internal functions
- Calculate the area under the balanced precision-recall curve (AUBPRC)
- New vignette for visualizing performance and feature importance
- Precision should be 1 when TP=1 and FP=0
- Factor levels in outcome column are not preserved
- Preprocessing in run_ml? HOT 1
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