Selective value coupling learning for detecting outliers in high-dimensional categorical data

• Main Authors: PANG, Guansong, XU, Hongzuo, CAO Longbing, ZHAO, Wentao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Outlier Detection; High-Dimensional Data; Categorical Data; Feature Selection; Coupling Learning; Databases and Information Systems; Data Storage Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7142; https://ink.library.smu.edu.sg/context/sis_research/article/8145/viewcontent/3132847.3132994.pdf
• Institution: Singapore Management University

This paper introduces a novel framework, namely SelectVC and its instance POP, for learning selective value couplings (i.e., interactions between the full value set and a set of outlying values) to identify outliers in high-dimensional categorical data. Existing outlier detection methods work on a f...