Correction: Understanding overfitting in random forest for probability estimation: a visualization and simulation study

Diagnostic and Prognostic Research, vol. 9, pp. 9

Abstract

status: Published

Authors 5

1. Lasai Barreñada

   KU Leuven

   Affiliation as printed

   Department of Development and Regeneration, Louvain, KU, Belgium

   Leuven Unit for Health Technology Assessment Research (LUHTAR), Louvain, KU, Belgium

2. Paula Dhiman

   University of Oxford

   Affiliation as printed

   Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK

3. Dirk Timmerman

   Universitair Ziekenhuis Leuven · KU Leuven

   Affiliation as printed

   Department of Development and Regeneration, Louvain, KU, Belgium

   Department of Obstetrics and Gynecology, University Hospitals Leuven, Louvain, Belgium

4. Anne‐Laure Boulesteix

   Munich Center for Machine Learning · Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie · Ludwig-Maximilians-Universität München

   Affiliation as printed

   Institute for Medical Information Processing, Biometry and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany

   Munich Center for Machine Learning, Munich, Germany

5. Ben Van Calster corresponding Aachen Department of Biomedical Data Sciences

   Leiden University · Leiden University Medical Center · KU Leuven

   Affiliation as printed

   Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands. ben.vancalster@kuleuven.be

   Department of Development and Regeneration, Louvain, KU, Belgium. ben.vancalster@kuleuven.be

   Leuven Unit for Health Technology Assessment Research (LUHTAR), Louvain, KU, Belgium. ben.vancalster@kuleuven.be