An Introspective Comparison of Random Forest-Based Classifiers for the Analysis of Cluster-Correlated Data by Way of RF++
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DOI: 10.1371/journal.pone.0007087
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Cited by:
- Oliver Hümbelin & Lukas Hobi & Robert Fluder, 2021. "Rich Cities, Poor Countryside? Social Structure of the Poor and Poverty Risks in Urban and Rural Places in an Affluent Country. An Administrative Data based Analysis using Random Forest," University of Bern Social Sciences Working Papers 40, University of Bern, Department of Social Sciences, revised 10 Nov 2021.
- Werner Adler & Sergej Potapov & Berthold Lausen, 2011. "Classification of repeated measurements data using tree-based ensemble methods," Computational Statistics, Springer, vol. 26(2), pages 355-369, June.
- Adler, Werner & Brenning, Alexander & Potapov, Sergej & Schmid, Matthias & Lausen, Berthold, 2011. "Ensemble classification of paired data," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1933-1941, May.
- Honoria Ocagli & Daniele Bottigliengo & Giulia Lorenzoni & Danila Azzolina & Aslihan S. Acar & Silvia Sorgato & Lucia Stivanello & Mario Degan & Dario Gregori, 2021. "A Machine Learning Approach for Investigating Delirium as a Multifactorial Syndrome," IJERPH, MDPI, vol. 18(13), pages 1-13, July.
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