Comparison of Multiway Discretization Algorithms for Data Mining
Jeong-Suk Kim, Young-Mi Jang, Jong-Hwa Na · Journal of the Korean Data and Information Science Society · 2005
The discretization algorithms for continuous data have been actively studied in the area of data mining. These discretizations are very important in data analysis, especially for efficient model selection in data mining. So, in this paper, we introduce the principles of some mutiway discretization algorithms including KEX, 1R and CN4 algorithm and investigate the efficiency of these algorithms through numerical study. For various underlying distribution, we compare these algorithms in view of misclassification rate.