Abstract—H1N1 virus and H3N2 virus was once a widespread epidemic in South Korea. The former was spread through human while the latter was spread via dogs. Those two viruses were widely spread in Korea in the same time. Also, those two viruses gave Koreans significant shock. As there wasn’t suitable vaccine or medication, Koreans have to be in fear about epidemic viruses. As both of two viruses was spread in Korea same period, and had many patients, we thought that H1N1 virus and H3N2 virus might have lots of common traits, so we started to analyze the viruses. To compare characteristics of two viruses, we concerned several algorithms. To find general rules from characteristic-unknown viruses, we think apriori algorithm is proper rather than Support Vector Machine. After experiment with apriori algorithm, we decided to find proper rules using tree structure. So, we used Decision Tree to extract specific rules of two viruses. Using a decision tree and apriori algorithm in our experiment, it was possible for us to compare the characteristics of H1N1 and H3N2 viruses.
Index Terms—H1N1 virus, H3N2 virus, the apriori algorithm, decision tree.
Seongpil Jang, Hunseok Choi, Yeonje Jung, Eoram Moon, and Taeseon Yoon are with the Department of Nature Science, Hankuk Academy of Foreign Studies, Gyeonggi, South Korea (e-mail: kiml11@daum.net, juyoung274@naver.com, tsyoon@hafs.hs.kr).
Cite: Seongpil Jang, Hunseok Choi, Yeonje Jung, Eoram Moon, and Taeseon Yoon, "A Comparison of H1N1 and H3N2 Viruses Using Decision Tree and Apriori Algorithm," International Journal of Machine Learning and Computing vol.6, no. 1, pp. 76-79, 2016.