Multiple Regression Ensembles

Multiple Regression Ensembles is a machine learning framework that combines the predictions of multiple regression models through ensemble techniques to improve overall predictive accuracy and robustness in regression tasks.

32

Publications

1.5K

Citations

103

Authors

54

Institutions

Publications per year

2017–2026

17

Authors

103

  1. SD
    Sašo Džeroski

    Jožef Stefan Institute, Slovenia

    2 publications · 145 citations

    2

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  2. TA
    Timo Aho

    2 publications · 108 citations

    2

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  3. JM
    Jose M. Moyano

    University of Córdoba, Spain

    2 publications · 45 citations

    2

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  4. HT
    Hannes Taubenböck

    Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Germany

    2 publications · 67 citations

    2

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  5. PA
    Patrick Aravena Pelizari

    Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Germany

    2 publications · 67 citations

    2

    h-index

1–5 of 103

Venues

  1. 2

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  2. Knowledge-Based Systems

    2 publications · 96 citations

    2

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  3. arXiv (Cornell University)

    Repository · 2 publications · 206 citations

    2

    h-index

  4. Climate Research

    1 publications · 15 citations

    1

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  5. Construction and Building Materials

    1 publications · 41 citations

    1

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1–5