Supervised Outlier Detection
Supervised Outlier Detection is a type of outlier detection method that belongs to the class of supervised learning approaches, distinguished by its reliance on labeled training data containing both normal and anomalous instances to learn a model capable of classifying new instances as either normal or outliers.
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2017–2026
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Zayed University
Abu Dhabi, United Arab Emirates
2 h-index
2 publications
31 citations

Northeastern University
Shenyang, China
2 h-index
6 publications
114 citations

Aarhus University
Aarhus, Denmark
2 h-index
5 publications
146 citations
Princeton University
Princeton, United States
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3 publications
133 citations
New York University Abu Dhabi
Abu Dhabi, United Arab Emirates
1 h-index
1 publications
12 citations
Vellore Institute of Technology University
Vellore, India
1 h-index
1 publications
51 citations

The University of Sydney
Sydney, Australia
1 h-index
1 publications
35 citations
Jaypee University of Information Technology
Solan, India
1 h-index
1 publications
15 citations
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Repository · 3 publications · 102 citations
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IDA · 1 publications · 11 citations
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1 publications · 50 citations
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