Hongze Qiu

Work place: Shandong University/School of Computer Science and Technology, Jinan, China

E-mail: qiuhze@sdu.edu.cn


Research Interests: Artificial Intelligence, Computer Architecture and Organization, Distributed Computing, Data Structures and Algorithms, Mathematics of Computing


Hongze Qiu received M.Sc. degrees in Computer studies from Fudan University. He is an Associate Professor of School of Computer Science and Technology at Shandong University. His current research interests include distributed computing, artificial intelligence, and genetic algorithm. 

Author Articles
Fuzzy SLIQ Decision Tree Based on Classification Sensitivity

By Hongze Qiu Haitang Zhang

DOI: https://doi.org/10.5815/ijmecs.2011.05.03, Pub. Date: 8 Oct. 2011

The determination of membership function is fairly critical to fuzzy decision tree induction. Unfortunately, generally used heuristics, such as SLIQ, show the pathological behavior of the attribute tests at split nodes inclining to select a crisp partition. Hence, for induction of binary fuzzy tree, this paper proposes a method depending on the sensitivity degree of attributes to all classes of training examples to determine the transition region of membership function. The method, properly using the pathological characteristic of common heuristics, overcomes drawbacks of G-FDT algorithm proposed by B. Chandra, and it well remedies defects brought on by the pathological behavior. Moreover, the sensitivity degree based algorithm outperforms G-FDT algorithm in respect to classification accuracy.

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