activity
20182026
most citedMachine Learning for Multi-Output Regression: When should a holistic multivariate approach be preferred over separate univariate ones?

9 citations · 36 across the 15 of their papers we have counts for

collaborators

16 papers

stat.AP2026

Text Data Analysis and Classification Methods - Insights from Customer Letters in Life Insurance

Andreas Groll, Marie Punsmann, Leonid Zeldin

The business of life insurance companies is characterized by long-term contracts. For this reason, data describing customers is of immense value. A portion of the data provided to…

stat.ME2026

Model-based bootstrap inference for Cox models after Lasso selection

Lena Schemet, Andreas Groll, Sarah Friedrich-Welz

Inference after variable selection in Cox regression is difficult because simple Wald-type intervals after selection can have poor finite-sample conditional coverage. We study a mo…

cs.LG2024

Modeling and Prediction of the UEFA EURO 2024 via Combined Statistical Learning Approaches

Andreas Groll, Lars M. Hvattum, Christophe Ley +3

In this work, three fundamentally different machine learning models are combined to create a new, joint model for forecasting the UEFA EURO 2024. Therefore, a generalized linear mo…

stat.ME2023

Statistically Enhanced Learning: a feature engineering framework to boost (any) learning algorithms

Florian Felice, Christophe Ley, Andreas Groll +1

Feature engineering is of critical importance in the field of Data Science. While any data scientist knows the importance of rigorously preparing data to obtain good performing mod…

stat.ML2022★ 3 cited

Churn modeling of life insurance policies via statistical and machine learning methods -- Analysis of important features

Andreas Groll, Carsten Wasserfuhr, Leonid Zeldin

Life assurance companies typically possess a wealth of data covering multiple systems and databases. These data are often used for analyzing the past and for describing the present…

stat.ML2022★ 9 cited

Machine Learning for Multi-Output Regression: When should a holistic multivariate approach be preferred over separate univariate ones?

Lena Schmid, Alexander Gerharz, Andreas Groll +1

Tree-based ensembles such as the Random Forest are modern classics among statistical learning methods. In particular, they are used for predicting univariate responses. In case of…