Discovery of Strong Association Rules for Attributes from Data for Program of All-Inclusive Care for the Elderly (PACE)

Journal of Systemics, Cybernetics and Informatics

Alfred Sears¹  Thomas Hahn¹  Shen Lu¹  Joseph Radich¹  Richard Segall¹ 

[1] ;

关键词: information gain;    Data Analysis;    decision tree;    association rules, classification rules;   

DOI  :  

来源: DOAJ

【 摘 要 】

The Program of All-Inclusive Care for the Elderly (PACE) (2013)[6] study aimed to find out if the program we designed for the 11 month treatment can efficiently help people lose weight, and even can keep tracking of weight loss and body fat by checking some of the parameters we measured during the 11 months. We worked on the potentially significant parameters for weight loss in 11 months, such as age, height, weight, body size and body fat. We used association rule mining and classification rule mining to discover which parameters are significant for weight loss and what are the associations between weight loss and those significant parameters. Experimental results showed that weight loss with support from 0.2 to 0.9 and confidence from 0.7 to 1.0 is related to body weight and the changes of chest size, arm size, waist size, thigh size and hip size. In future, we will discover the associations among body weight, body size, body fat, heart beat and blood pressure.

【 授权许可】

Unknown