Ding-An Chiang This email address is being protected from spambots. You need JavaScript enabled to view it.1, Cheng-Tzu Wang2 , Yi-Hsin Wang3 and Chun-Chi Chen1
1Department of Computer Science and Information Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C. 2Department of Computer Science, National Taipei University of Education, Taipei, Taiwan 106, R.O.C. 3Department of Information Management, Chang Gung Institute of Technology, Taiwan, R.O.C
Received: October 31, 2008 Accepted: April 30, 2009 Publication Date: December 1, 2010
In this paper, we use decision tree to establish a yield improvement model for glass sputtering process; however, the tree may have irrelevant values problem. In other words, when the tree is represented by a set of rules, not only comprehensibility of the resultant rules will be detracted but also critical factors of the manufacturing process cannot be effectively identified. From the performance issue and practical issue, we have to remove irrelevant conditions from the rules; otherwise, a domain expert is needed to review the decision tree. In this paper, we use a very simple example to demonstrate this point of view. Moreover, to identify and remove irrelevant conditions from the rules, we also revise Chiang’s previous algorithm such that the modified algorithm can deal not only discrete data but also quantitative data.
Keywords: Data Mining, Decision Tree, The Irrelevant Values Problem, Glass Sputtering Process, Yield Analysis
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