Machine Learning Forecast Combination

Machine Learning Forecast Combination is a forecast combination method that employs machine learning algorithms to non-linearly aggregate predictions from multiple individual forecasting models, distinguishing itself from traditional linear or equal-weight approaches by adaptively learning optimal weighting structures from data.

65

Publications

3.2K

Citations

173

Authors

111

Institutions

Publications per year

2017–2026

36

Authors

173

  1. MJ
    Mark J. Kamstra

    York University, Canada

    3 publications · 291 citations

    3

    h-index

  2. SJ
    Salvatore Joseph Terregrossa

    Istanbul Aydın University, Türkiye

    2 publications · 48 citations

    2

    h-index

  3. MH
    M. Hashem Pesaran

    University of Southern California, United States

    2 publications · 52 citations

    2

    h-index

  4. WS
    Wei Sun

    University of Regina, Canada

    2 publications · 94 citations

    2

    h-index

  5. JW
    Jianzhou Wang

    Dongbei University of Finance and Economics, China

    2 publications · 382 citations

    2

    h-index

1–5 of 173

Venues

  1. International Journal of Forecasting

    6 publications · 453 citations

    6

    h-index

  2. Journal of Forecasting

    3 publications · 321 citations

    3

    h-index

  3. National Institute Economic Review

    2 publications · 52 citations

    2

    h-index

  4. IEEE Access

    2 publications · 32 citations

    2

    h-index

  5. Algorithms

    2 publications · 57 citations

    2

    h-index

1–5