Correction to “Assessing agreement between permutation and dropout variable importance methods for regression and random forest models” [Electronic Research Archieve 32(7) (2024) 4495–4514]

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This article has been updated. A Correction to this article was published on .

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The Original Article was published on

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The Original Article was published on

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This article has been updated

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This article was retracted on

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This article has been updated

Abstract

Following publication of this article [1], we identified an error in the presentation and interpretation of the out-of-bag permutation-and-predict variable importance results shown in Figures 4 and 6. The quantity labeled and discussed as OOB PaP was, in fact, a scaled version of the measure. As a result, the figures and portions of the accompanying discussion did not represent the unscaled OOB PaP metric. Figures 4 and 6 have been updated to include both the raw unscaled OOB PaP measure and the scaled version, OOB scale. The corrected versions of Figures 4 and 6 are reproduced below. Corresponding revisions have been made to the discussion and conclusions. Specifically, several statements previously attributed to OOB PaP should instead be attributed to OOB scale. The revised manuscript also includes discussion of the behavior of the unscaled OOB PaP metric. These corrections do not affect the underlying analyses, methodology, or overall conclusions of the study regarding the relationships among variable importance measures. Rather, they provide a more accurate characterization of the behavior of the out-of-bag permutation-based importance metrics. Additionally, Figures 7–10 have been updated to improve clarity and reduce redundant plotting information.

CHANGE HISTORY

A Correction to this paper has been published:
https://doi.org

The Retraction Note was updated to reflect reception of statements of disagreement from all authors.

This article has been retracted.Please see the Retraction Notice for more detail:
https://doi.org

References

[1] K. Bladen, D. Richard Cutler, Assessing agreement between permutation and dropout variable importance methods for regression and random forest models, Electron. Res. Arch., 32 (2024), 4495-4514. https://doi.org/10.3934/era.2024203