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
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2018
• 主題: Outlier Detection; Outlier Ensemble; Feature Selection; Sparse Modeling; Sequential Ensemble; Databases and Information Systems; Data Storage Systems
• 在線閱讀: 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

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...