Sparse modeling-based sequential ensemble learning for effective outlier detection in high-dimensional numeric data

• Main Authors: PANG, Guansong, CAO, Longbing, CHEN, Ling, LIAN, Defu, LIU, Huan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Outlier Detection; Outlier Ensemble; Feature Selection; Sparse Modeling; Sequential Ensemble; Databases and Information Systems; Data Storage Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7140; https://ink.library.smu.edu.sg/context/sis_research/article/8143/viewcontent/11692_Article_Text_15220_1_2_20201228.pdf
• Institution: Singapore Management University

The large proportion of irrelevant or noisy features in reallife high-dimensional data presents a significant challenge to subspace/feature selection-based high-dimensional outlier detection (a.k.a. outlier scoring) methods. These methods often perform the two dependent tasks: relevant feature subse...