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Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests

In an interesting and quite exhaustive review on Random Forests (RF) methodology in bioinformatics Touw et al. address—among other topics—the problem of the detection of interactions between variables based on RF methodology. We feel that some important statistical concepts, such as ‘interaction’, ‘...

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Detalles Bibliográficos
Autores principales: Boulesteix, Anne-Laure, Janitza, Silke, Hapfelmeier, Alexander, Van Steen, Kristel, Strobl, Carolin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4364067/
https://www.ncbi.nlm.nih.gov/pubmed/24723569
http://dx.doi.org/10.1093/bib/bbu012
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author Boulesteix, Anne-Laure
Janitza, Silke
Hapfelmeier, Alexander
Van Steen, Kristel
Strobl, Carolin
author_facet Boulesteix, Anne-Laure
Janitza, Silke
Hapfelmeier, Alexander
Van Steen, Kristel
Strobl, Carolin
author_sort Boulesteix, Anne-Laure
collection PubMed
description In an interesting and quite exhaustive review on Random Forests (RF) methodology in bioinformatics Touw et al. address—among other topics—the problem of the detection of interactions between variables based on RF methodology. We feel that some important statistical concepts, such as ‘interaction’, ‘conditional dependence’ or ‘correlation’, are sometimes employed inconsistently in the bioinformatics literature in general and in the literature on RF in particular. In this letter to the Editor, we aim to clarify some of the central statistical concepts and point out some confusing interpretations concerning RF given by Touw et al. and other authors.
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spelling pubmed-43640672015-03-25 Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests Boulesteix, Anne-Laure Janitza, Silke Hapfelmeier, Alexander Van Steen, Kristel Strobl, Carolin Brief Bioinform Papers In an interesting and quite exhaustive review on Random Forests (RF) methodology in bioinformatics Touw et al. address—among other topics—the problem of the detection of interactions between variables based on RF methodology. We feel that some important statistical concepts, such as ‘interaction’, ‘conditional dependence’ or ‘correlation’, are sometimes employed inconsistently in the bioinformatics literature in general and in the literature on RF in particular. In this letter to the Editor, we aim to clarify some of the central statistical concepts and point out some confusing interpretations concerning RF given by Touw et al. and other authors. Oxford University Press 2015-03 2014-04-09 /pmc/articles/PMC4364067/ /pubmed/24723569 http://dx.doi.org/10.1093/bib/bbu012 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Papers
Boulesteix, Anne-Laure
Janitza, Silke
Hapfelmeier, Alexander
Van Steen, Kristel
Strobl, Carolin
Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests
title Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests
title_full Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests
title_fullStr Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests
title_full_unstemmed Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests
title_short Letter to the Editor: On the term ‘interaction’ and related phrases in the literature on Random Forests
title_sort letter to the editor: on the term ‘interaction’ and related phrases in the literature on random forests
topic Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4364067/
https://www.ncbi.nlm.nih.gov/pubmed/24723569
http://dx.doi.org/10.1093/bib/bbu012
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