Ridge Regression

Ridge Regression is a regularized linear regression method that belongs to the class of shrinkage estimators, distinguished by its use of an L2 penalty on the coefficients to mitigate multicollinearity and prevent overfit Practicing multicollinearity and overfitting.

2K

Publications

237.3K

Citations

5K

Authors

1.8K

Institutions

Publications per year

2017–2026

967

Parents

Authors

5K

  1. BM
    B. M. Golam Kibria

    Florida International University, United States

    28 publications · 2.3K citations

    23

    h-index

  2. AF
    Adewale F. Lukman

    Landmark University, Nigeria

    19 publications · 882 citations

    16

    h-index

  3. GS
    Ghazi Shukur

    Jönköping University, Sweden

    16 publications · 1.4K citations

    15

    h-index

  4. ‎A
    ‎M‎ohammad Arashi

    University of Shahrood, Iran

    21 publications · 621 citations

    14

    h-index

  5. JH
    John H. Kalivas

    Idaho State University, United States

    15 publications · 548 citations

    14

    h-index

1–5 of 5K

Venues

  1. Technometrics

    59 publications · 35.1K citations

    35

    h-index

  2. Communication in Statistics- Theory and Methods

    76 publications · 5.2K citations

    30

    h-index

  3. arXiv (Cornell University)

    Repository · 87 publications · 4.1K citations

    30

    h-index

  4. Journal of the American Statistical Association

    39 publications · 3.8K citations

    29

    h-index

  5. 28

    h-index

1–5