An Outlier Detection Approach Based on Improved Self-Organizing Feature Map Clustering Algorithm

An Outlier Detection Approach Based on Improved Self-Organizing Feature Map Clustering Algorithm

Local Outlier Factor (LOF) outlier detecting algorithm has good accuracy in detecting global and local outliers. However, the algorithm needs to traverse the entire dataset when calculating the local outlier factor of each data point, which adds extra time overhead and makes the algorithm execution...

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Bibliographic Details
Main Authors: Ping Yang, Dan Wang, Zhuojun Wei, Xiaolin Du, Tong Li
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Canopy
cluster
outlier detection
LOF
SOFM
Online Access:https://ieeexplore.ieee.org/document/8735734/

Internet

https://ieeexplore.ieee.org/document/8735734/

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