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Category Variable Selection Method for Efficient Clustering

  • Heo, Jun (Dept. of Information and Communication, Kyungmin University) ;
  • Kim, Chae Yun (Dept. of Medical IT Marketing, Eulji University) ;
  • Jung, Yong-Gyu (Dept. of Medical IT Marketing, Eulji University)
  • Received : 2013.09.01
  • Published : 2013.11.30

Abstract

Recent medical industry is an aging society and the application of national health insurance, with state-of-the-art research and development, including the pharmaceutical market is greatly increased. The nation's health care industry through new support expansion and improve the quality of life for the research and development will be needed. In addition, systemic administration of basic medical supplies, or drugs are needed, the drug at the same time managing how systematic analysis of pharmaceutical ingredients, based on data through the purchase of new medicines and pharmaceutical ingredients automatically classified by analyzing the statistics of drug purchases and the future a system that can predict a patient is needed. In this study, the drugs to the patient according to the component analysis and predictions for future research techniques, k-means clustering and k-NN (Nearest Neighbor) Comparative studies through experiments using the techniques employ a more efficient method to study how to proceed. In this study, the effects of the drugs according to the respective components in time according to the number of pieces in accordance with the patient by analyzing the statistics by predicting future patient better medical industry can be built.

Keywords

Drug component analysis;clustering;k-means;k-NN

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