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
2.1K
Robust Regression and Outlier Detection
Gregory F. Piepel, Peter J. Rousseeuw, Annick M. Leroy · Technometrics · 1989 · 6.2K citations
Procedures for Detecting Outlying Observations in Samples
Frank E. Grubbs · Technometrics · 1969 · 3.7K citations
A Survey of Outlier Detection Methodologies
Jim Austin · Artificial Intelligence Review · 2004 · 3.3K citations · Full text
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London School of Economics and Political Science, United Kingdom
12 publications · 2.4K citations
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1.9K
Tsinghua University
Beijing, China
17 h-index
46 publications
2.7K citations

Chinese Academy of Sciences
Beijing, China
17 h-index
48 publications
3.3K citations
KU Leuven
Leuven, Belgium
16 h-index
39 publications
4.2K citations

University of Alberta
Edmonton, Canada
15 h-index
29 publications
3.7K citations
Wuhan University
Wuhan, China
15 h-index
33 publications
1.7K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
14 h-index
19 publications
1.7K citations
Virginia Tech
Blacksburg, United States
14 h-index
29 publications
2K citations
National University of Singapore
Singapore, Singapore
13 h-index
31 publications
8.9K citations
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57 publications · 15.3K citations
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26 publications · 5.1K citations
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CSDA · 21 publications · 2.3K citations
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24 publications · 850 citations
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24 publications · 926 citations
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