Tensor factorization for missing data imputation in medical questionnaires

• Main Authors: Dauwels, Justin, Garg, Lalit, Earnest, Arul, Pang, Leong Khai
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/98569; http://hdl.handle.net/10220/13419
• Institution: Nanyang Technological University

This paper presents innovative collaborative filtering techniques to complete missing data in repeated medical questionnaires. The proposed techniques are based on the canonical polyadic (CP) decomposition (a.k.a. PARAFAC). Besides the standard CP decomposition, also a normalized decomposition is ut...