Identification of Outliers in Graph Signals*
© 2019 IEEE. Outlier detection, or the identification of observations that differ significantly from the norm, is an important aspect of data mining. Conventional outlier detection tools have limited applicability to networks, in which there are interdependencies between the variables. In this paper...
Format: | Article |
---|---|
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2021
|
Online Access: | https://hdl.handle.net/1721.1/137191 |
Similar Items
-
Identification of Outliers in Graph Signals*
by: Gopalakrishnan, Karthik, et al.
Published: (2022) -
Dissimilarity algorithm on conceptual graphs to mine text outliers
by: Kamaruddin, Siti Sakira, et al.
Published: (2009) -
Graph-Theoretic Outlier Rejection: From Instance
to Category-Level Perception
by: Shi, Jingnan
Published: (2022) -
Differentially Private Outlier Detection in Multivariate Gaussian Signals
by: Degue, Kwassi H, et al.
Published: (2022) -
The performance of Diagnostic-Robust F in the identification of multivariate outliers.
by: Midi, Habshah