33 citations · 34 across the 4 of their papers we have counts for
4 papers
Unity Forests: Improving Interaction Modelling and Interpretability in Random Forests
Roman Hornung, Alexander Hapfelmeier
Random forests (RFs) are widely used for prediction and variable importance analysis and are often believed to capture any types of interactions via recursive splitting. However, s…
Multi forests: Variable importance for multi-class outcomes
Roman Hornung, Alexander Hapfelmeier
In prediction tasks with multi-class outcomes, identifying covariates specifically associated with one or more outcome classes can be important. Conventional variable importance me…
Tree models for assessing covariate-dependent method agreement
Siranush Karapetyan, Achim Zeileis, André Henriksen +1
Method comparison studies explore the agreement of measurements made by two or more methods. Commonly, agreement is evaluated by the well-established Bland-Altman analysis. However…
Sequential Permutation Testing of Random Forest Variable Importance Measures
Alexander Hapfelmeier, Roman Hornung, Bernhard Haller
Hypothesis testing of random forest (RF) variable importance measures (VIMP) remains the subject of ongoing research. Among recent developments, heuristic approaches to parametric…