A research of data stratification algorithm based on semi-supervised clustering

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.