Man pages for iml
Interpretable Machine Learning
| calculate.ale.cat | Compute ALE for 1 categorical feature |
| calculate.ale.num | Compute ALE for 1 numerical feature |
| calculate.ale.num.cat | Compute ALE for 2 features, one numerical, one categorical |
| calculate.ale.num.num | Compute ALE for 2 numerical features |
| extract.glmnet.effects | Extract glmnet effects |
| FeatureEffect | Effect of a feature on predictions |
| FeatureEffects | Effect of a feature on predictions |
| FeatureImp | Feature importance |
| has.predict | returns TRUE if object has predict function |
| iml-package | Make machine learning models and predictions interpretable |
| impute_cells | Impute missing cells of grid |
| Interaction | Feature interactions |
| InterpretationMethod | Interpretation Method |
| LocalModel | LocalModel |
| order_levels | Order levels of a categorical features |
| Partial | Effect of one or two feature(s) on the model predictions... |
| plot.FeatureEffect | Plot FeatureEffect |
| plot.FeatureEffects | Plot FeatureEffect |
| plot.FeatureImp | Plot Feature Importance |
| plot.Interaction | Plot Interaction |
| plot.LocalModel | Plot Local Model |
| plot.Shapley | Plot Shapley |
| plot.TreeSurrogate | Plot Tree Surrogate |
| predict.LocalModel | Predict LocalModel |
| Predictor | Predictor object |
| predict.TreeSurrogate | Predict Tree Surrogate |
| probs.to.labels | Turn class probabilities into class labels |
| Shapley | Prediction explanations with game theory |
| TreeSurrogate | Decision tree surrogate model |
