Risk prediction with machine learning and regression methods

Ewout Steyerberg; T van der Ploeg; BJ Calster

doi:10.1002/bimj.201300297

Risk prediction with machine learning and regression methods

Ewout Steyerberg, T van der Ploeg, BJ Calster

Public Health

Research output: Contribution to journal › Article › Academic › peer-review

67 Citations (Scopus)

Abstract

This is a discussion of issues in risk prediction based on the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gerard Biau, Michael Kohler, Inke R. Konig, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. Konig, and Andreas Ziegler.

Original language	Undefined/Unknown
Pages (from-to)	601-606
Number of pages	6
Journal	Biometrical Journal
Volume	56
Issue number	4
DOIs	https://doi.org/10.1002/bimj.201300297
Publication status	Published - 2014

Research programs

EMC NIHES-02-65-01

Access to Document

10.1002/bimj.201300297

http://hdl.handle.net/1765/60645

Cite this

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title = "Risk prediction with machine learning and regression methods",

abstract = "This is a discussion of issues in risk prediction based on the following papers: {"}Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory{"} by Jochen Kruppa, Yufeng Liu, Gerard Biau, Michael Kohler, Inke R. Konig, James D. Malley, and Andreas Ziegler; and {"}Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications{"} by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. Konig, and Andreas Ziegler.",

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AU - Steyerberg, Ewout

AU - van der Ploeg, T

AU - Calster, BJ

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N2 - This is a discussion of issues in risk prediction based on the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gerard Biau, Michael Kohler, Inke R. Konig, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. Konig, and Andreas Ziegler.

AB - This is a discussion of issues in risk prediction based on the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gerard Biau, Michael Kohler, Inke R. Konig, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. Konig, and Andreas Ziegler.

U2 - 10.1002/bimj.201300297

DO - 10.1002/bimj.201300297

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