- Volume 20 Issue 6
In the field of data mining technique, there are various methods such as association rules, cluster analysis, decision tree, neural network. Among them, association rules are defined by using various association evaluation criteria such as support, confidence, and lift. Agrawal et al. (1993) first proposed this association rule, and since then research has been conducted by many scholars. Recently, studies related to crossover entropy have been published (Park, 2016b). In this paper, we proposed a purely symmetric J measure considering directionality and purity in the previously published J measure, and examined its usefulness by using examples. As a result, it is found that the pure symmetric J measure changes more clearly than the conventional J measure, the symmetric J measure, and the pure crossover entropy measure as the frequency of coincidence increases. The variation of the pure symmetric J measure was also larger depending on the magnitude of the inconsistency, and the presence or absence of the association was more clearly understood.
- Agrawal, R., Imielinski, R., Swami, A. (1993). Mining association rules between sets of items in large databases, Proceedings of the ACM SIGMOD Conference on Management of Data, 207-216.
- Chun, I. J., Eun, H. C. (2014). Association rule mining on viewing rate analysis : in case of drama genre of terrestrial broadcasters, Korean Journal of Journalism & Communication Studies, 58(5), 391-416. (in Korean).
- Park, H. C. (2013). A proposition of association rule thresholds considering relative occurrence/nonoccurrence, Journal of the Korean Data Analysis Society, 15(4), 1841-1850. (in Korean).
- Park, H. C. (2014). Comparison of confidence measures useful for classification model building, Journal of the Korean Data and Information Science Society, 25(2), 365-371. (in Korean). https://doi.org/10.7465/jkdi.2014.25.2.365
- Park, H. C. (2016a). Proposition of entropy based association thresholds, Journal of the Korean Data Analysis Society, 18(4), 1905-1914. (in Korean).
- Park, H. C. (2016b). Proposition of pure signed Hellinger measure as association rule threshold, Journal of the Korean Data Analysis Society, 18(5), 2477-2484. (in Korean).
- Park, H. C. (2017a). Alternative plan of elementary association threshold by symmetric J measure, Journal of the Korean Data Analysis Society, 19(4), 1887-1895. (in Korean).
- Park, H. C. (2017b). Proposition of adjusted balance Hellinger measure as interestingness measure, Journal of the Korean Data Analysis Society, 19(4), 1887-1895. (in Korean).
- Park, H. C. (2018). Proposition of pure cross entropy in association rule technique, Journal of the Korean Data Analysis Society, 20(2), 669-679. (in Korean).
- Smyth, P., Goodman, R. M. (1992). An information theoretic approach to rule induction from databases, IEEE Transactions on Knowledge and Data Engineering, 4(4), 301-316. https://doi.org/10.1109/69.149926