Multi-view cluster analysis with incomplete data to understand treatment effects

• Published in: Information sciences Vol. 494; pp. 278 - 293
• Main Authors: Chao, Guoqing, Sun, Jiangwen, Lu, Jin, Wang, An-Li, Langleben, Daniel D., Li, Chiang-Shan, Bi, Jinbo
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.08.2019
• Subjects: Co-clustering; Granular computing; Missing value; Multi-view data analysis; Opioid addiction; Opioid addiction; Granular computing; Missing value; Multi-view data analysis; Co-clustering

Multi-view cluster analysis, as a popular granular computing method, aims to partition sample subjects into consistent clusters across different views in which the subjects are characterized. Frequently, data entries can be missing from some of the views. The latest multi-view co-clustering methods...