James-stein Encoding

James-Stein Encoding is a categorical encoding technique that shrinks group-wise estimates toward a global mean using the James-Stein estimator, thereby reducing variance and improving predictive accuracy in high-cardinality categorical variables.

6

Publications

367

Citations

9

Authors

10

Institutions

Publications per year

2017–2026

0

Authors

9

  1. JP
    Jerome P. Keating

    The University of Texas at San Antonio, United States

    2 publications · 55 citations

    2

    h-index

  2. RM
    Robert Mason

    Southwest Research Institute, United States

    2 publications · 55 citations

    2

    h-index

  3. NR
    Norman R. Draper

    University of Wisconsin–Madison, United States

    2 publications · 268 citations

    2

    h-index

  4. JT
    J. T. Gene Hwang

    Cornell University, United States

    1 publications · 33 citations

    1

    h-index

  5. AU
    Aman Ullah

    University of California, Riverside, United States

    1 publications · 33 citations

    1

    h-index

1–5 of 9

Venues

  1. Technometrics

    2 publications · 268 citations

    2

    h-index

  2. The American Statistician

    2 publications · 55 citations

    2

    h-index

  3. Journal of Econometrics

    1 publications · 33 citations

    1

    h-index

  4. 1

    h-index

1–4