A Mass-Based Approach for Local Outlier Detection

A Mass-Based Approach for Local Outlier Detection

This paper proposes a new outlier detection approach that measures the degree of outlierness for each instance in a given dataset. The proposed model utilizes a mass-based dissimilarity measure to address the weaknesses of neighbor-based outlier models while detecting local outliers in the dataset w...

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Bibliographic Details
Main Authors: Anh Hoang, Toan Nguyen Mau, Duc-Vinh Vo, Van-Nam Huynh
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Outlier detection
mass-based dissimilarity
unsupervised learning
knowledge discovery
Online Access:https://ieeexplore.ieee.org/document/9328765/

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