Outlier Removal

Outlier Removal is a data preprocessing technique that fundamentally consists in the identification and exclusion of data points deviating significantly from the majority of observations to prevent undue influence on statistical analyses or machine learning models.

2.1K

Publications

167K

Citations

5.6K

Authors

1.9K

Institutions

Publications per year

2017–2026

779

Authors

5.6K

  1. PJ
    Peter J. Rousseeuw

    University of Antwerp, Belgium

    13 publications · 8.2K citations

    13

    h-index

  2. AC
    Anthony C. Atkinson

    London School of Economics and Political Science, United Kingdom

    12 publications · 2.4K citations

    12

    h-index

  3. BW
    Beata Walczak

    University of Silesia in Katowice, Poland

    9 publications · 457 citations

    9

    h-index

  4. FA
    Fabrizio Angiulli

    University of Calabria, Italy

    9 publications · 871 citations

    9

    h-index

  5. KW
    Keith Worden

    University of Sheffield, United Kingdom

    8 publications · 1.3K citations

    8

    h-index

1–5 of 5.6K

Venues

  1. Technometrics

    57 publications · 15.3K citations

    32

    h-index

  2. Journal of the American Statistical Association

    26 publications · 5.1K citations

    23

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 21 publications · 2.3K citations

    20

    h-index

  4. Expert Systems with Applications

    24 publications · 850 citations

    19

    h-index

  5. Chemometrics and Intelligent Laboratory Systems

    24 publications · 926 citations

    18

    h-index

1–5