CONDITIONAL FEATURE IMPORTANCE WITH GENERATIVE MODELING USING ADVERSARIAL RANDOM FORESTS

arXiv

Interpretable Machine Learning for Survival Analysis

arXiv

Model interpretation

Applied Machine Learning Using mlr3 in R

Fast Estimation of Partial Dependence Functions using Trees

arXiv

Non-sequential Pipelines and Tuning

Applied Machine Learning Using mlr3 in R

arfpy: A Python Package for Density Estimation and Generative Modeling with Adversarial Random Forests

Journal of Open Research Software

A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data

arXiv

Feature Selection

Applied Machine Learning Using mlr3 in R

Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation

Physiological Measurement

Random Survival Forests With Competing Events: A Subdistribution-Based Imputation Approach

Biometrical Journal

Conditional feature importance for mixed data

AStA Advances in Statistical Analysis

A Guide to Feature Importance Methods for Scientific Inference

Toward Understanding the Disagreement Problem in Neural Network Feature Attribution

A discovery and verification approach to pharmacovigilance using electronic healthcare data

Frontiers in Pharmacology

CountARFactuals - Generating Plausible Model-Agnostic Counterfactual Explanations with Adversarial Random Forests

Unfooling SHAP and SAGE: Knockoff Imputation for Shapley Values

Communications in Computer and Information Science

Unifying local and global model explanations by functional decomposition of low dimensional structures

Proceedings of The 26th International Conference on Artificial Intelligence and Statistics

Interpreting Deep Neural Networks with the Package innsight

arXiv

Decomposing Global Feature Effects Based on Feature Interactions

arXiv

Adversarial Random Forests for Density Estimation and Generative Modeling

Proceedings of The 26th International Conference on Artificial Intelligence and Statistics

Are SHAP Values Biased Towards High-Entropy Features?

survex: an R package for explaining machine learning survival models

Bioinformatics

Genetic associations vary across the spectrum of fasting serum insulin: results from the European IDEFICS/I.Family children's cohort

Diabetologia

Forest tree species distribution for Europe 2 2000-2020: mapping potential and realized 3 distributions using spatiotemporal Machine 4 Learning

Research Square

Special issue: Artificial intelligence in genomics

Human Genetics