CURE: Flexible categorical data representation by hierarchical coupling learning

• Main Authors: JIAN, Songlei, PANG, Guansong, CAO, Longbing, LU, Kai, GAO, Hang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Categorical data representation; unsupervised learning; coupling learning; non-IID learning; clustering; outlier detection; Databases and Information Systems; Data Storage Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7137; https://ink.library.smu.edu.sg/context/sis_research/article/8140/viewcontent/08395013.pdf
• Institution: Singapore Management University

The representation of categorical data with hierarchical value coupling relationships (i.e., various value-to-value cluster interactions) is very critical yet challenging for capturing complex data characteristics in learning tasks. This paper proposes a novel and flexible coupled unsupervised categ...