A Research of Data Stratification Algorithm based on Semi-supervised Clustering

被引：0
|
作者：
Yang, Shaobo [1 ]
Yu, Jianmin [1 ]
Liu, Yi [1 ]
机构：
[1] Beijing Inst Technol, Coll Informat & Elect, Beijing 100081, Peoples R China
来源：
PROCEEDINGS OF 2015 IEEE INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATCS AND COMPUTING (IEEE PIC) | 2015年
关键词：
Data processing; semi-supervised clustering; risk stratification; MKKZ-PCKmeans; RISK; TOOL;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel data stratification algorithm based on semi-supervised clustering algorithm was proposed. This proposed algorithm can automatically cluster undiagnosed people to no risk, low risk, medium risk and high risk level. Compared with traditional unsupervised clustering named K-Means algorithm and semi-supervised clustering methods that named Seeded Kmeans, COP-Kmeans and PC-Kmeans, the sensitivity of proposed method in this research, called MKKZ-PCKmeans, increased by about 11% as the results shown. This method can simply and quickly get the risk stratification of type II diabetes mellitus for the crowd who are unable to carry out the blood test. Meanwhile, this method can be used in other applications on data processing, especially in space information network.
引用
收藏
页码：196 / 200
页数：5
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