Journal of Applied Mathematics
Volume 2013 (2013), Article ID 350123, 8 pages
Research Article

An Algorithm for Discretization of Real Value Attributes Based on Interval Similarity

1School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China
2State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China
3Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway
4College of Engineering and Science, Victoria University, Melbourne, VIC 8001, Australia
5School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia

Received 3 November 2012; Accepted 25 February 2013

Academic Editor: Xiaojing Yang

Copyright © 2013 Li Zou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Discretization algorithm for real value attributes is of very important uses in many areas such as intelligence and machine learning. The algorithms related to Chi2 algorithm (includes modified Chi2 algorithm and extended Chi2 algorithm) are famous discretization algorithm exploiting the technique of probability and statistics. In this paper the algorithms are analyzed, and their drawback is pointed. Based on the analysis a new modified algorithm based on interval similarity is proposed. The new algorithm defines an interval similarity function which is regarded as a new merging standard in the process of discretization. At the same time, two important parameters (condition parameter and tiny move parameter ) in the process of discretization and discrepancy extent of a number of adjacent two intervals are given in the form of function. The related theory analysis and the experiment results show that the presented algorithm is effective.