Survival analysis is a subfield of statistics where the goal is to analyze and model data
where the outcome is the time until an event of interest occurs. One of the main challenges …

A decision tree is a predictive model that recursively partitions the covariate's space into
subspaces such that each subspace constitutes a basis for a different prediction function …

Generalized random forests Page 1 The Annals of Statistics 2019, Vol. 47, No. 2, 1148–1178
https://doi.org/10.1214/18-AOS1709 © Institute of Mathematical Statistics, 2019 GENERALIZED …

Decision trees have become one of the most powerful and popular approaches in
knowledge discovery and data mining; it is the science of exploring large and complex …

Background Prediction models for time-to-event outcomes are commonly used in biomedical
research to obtain subject-specific probabilities that aid in making important clinical care …

In recent years, a large variety of textbooks dealing with time-to-event analysis has been
published. Most of these books focus on the statistical analysis of observations in continuous …

This article provides a birds-eye view on the role of decision trees in machine learning and
data science over roughly four decades. It sketches the evolution of decision tree research …

The most popular approach for analyzing survival data is the Cox regression model. The
Cox model may, however, be misspecified, and its proportionality assumption may not …

There has been increasing concern within the machine learning community and beyond that
Artificial Intelligence (AI) faces a bias and discrimination crisis which needs AI fairness with …

Artificial intelligence (AI) is a scientific discipline that aims to create intelligent machines.
Machine learning is a popular and practical AI subfield that aims to automatically improve …