Feature Engineering For Forecasting

Feature Engineering for Forecasting is a methodological process in predictive analytics that involves the systematic creation, transformation, and selection of input variables from raw data to enhance the accuracy and efficiency of forecasting models within domains such as Cloud Forecasting and Short-Term Revenue Forecasting.

130

Publications

7.2K

Citations

441

Authors

219

Institutions

Publications per year

2017–2026

99

Authors

441

  1. MZ
    Marwin Züfle

    University of Würzburg, Germany

    2 publications · 44 citations

    2

    h-index

  2. NM
    Noura Metawa

    Mansoura University, Egypt

    2 publications · 38 citations

    2

    h-index

  3. SK
    Samuel Kounev

    University of Würzburg, Germany

    2 publications · 44 citations

    2

    h-index

  4. NH
    Nikolas Herbst

    University of Würzburg, Germany

    2 publications · 44 citations

    2

    h-index

  5. MZ
    M. Zulfiqar

    University of Engineering and Technology Lahore, Pakistan

    2 publications · 106 citations

    2

    h-index

1–5 of 441

Venues

  1. Expert Systems with Applications

    9 publications · 895 citations

    9

    h-index

  2. IEEE Access

    6 publications · 258 citations

    6

    h-index

  3. International Journal of Forecasting

    4 publications · 183 citations

    4

    h-index

  4. Neural Computing and Applications

    4 publications · 237 citations

    4

    h-index

  5. Energies

    3 publications · 81 citations

    3

    h-index

1–5