AN ALGORITHM FOR GENERATING FUZZY DECISION TREE BASED ON CENTER OF GRAVITY
The center of gravity (COG) of fuzzy sets is an essential feature that concurrently reflects the location and shape of the fuzzy sets concerned, this paper treated the COG as the core of any fuzzy membership function, and presented an algorithm based on the COG using the information entropy minimization heuristic for generating decision tree with fuzzy value attributes. By considering the center of gravity (COG) of the fuzzy value attribute and analyzing non-stable partition points, the presented algorithm gives us a desirable behavior of the information entropy of partitioning. To the unknown-classified sample data, the algorithm offers a rapid matching speed. Finally, the example on medical records that we collected in a hospital shows the utility of the proposed algorithm. Comparison to the heuristic algorithm 1|7|, thepresented algorithm based on the COG has a stronger generalizing ability.
Center of gravity ( COG ), Fuzzy value attribute Fuzzy decision tree Non-stable partition point
DONG-MEI HUANG JIE YANG Y A-MIN LI CHUN-LAN LI
College of Science, Agricultural University of Hebei, Baoding 071001, P.R.China Beijing University of Chinese Medicine, Beijing, 100029, P.R.China Artificial Intelligence Research Center, Agricultural University of Hebei, Baoding 071001
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
485-489
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）