A copula-based clustering algorithm to analyse EU country diets
作者：
Highlights：
• A novel copula-based clustering algorithm is suggested to group EU countries.
• Average calories of different food aggregates are used as segmentation variables.
• Complex multivariate associations in Countries dietary structures are identified.
• Changes towards a (un)common (un)healthier food dietary structure are investigated.
• Countries at risk of an increase in obesity and diet-related disease are identified.
摘要
•A novel copula-based clustering algorithm is suggested to group EU countries.•Average calories of different food aggregates are used as segmentation variables.•Complex multivariate associations in Countries dietary structures are identified.•Changes towards a (un)common (un)healthier food dietary structure are investigated.•Countries at risk of an increase in obesity and diet-related disease are identified.
论文关键词：Clustering,Coclust,Healthy diet,Convergence,Dietary energy,EU countries
论文评审过程：Received 30 December 2016, Revised 19 April 2017, Accepted 2 June 2017, Available online 6 June 2017, Version of Record 24 July 2017.
论文官网地址：https://doi.org/10.1016/j.knosys.2017.06.004
