模糊决策树推理是机器学习领域中的一种解决分类问题的有效算法,模糊推理方法的选择在很大程度上影响推理的性能和效果.对Min-Ambiguity,Fuzzy ID3和加权模糊决策树3种推理机制进行了对比研究,选择了推理过程中4种常用的算子(∨,∧)、(∨,×)、(+,∧)和(+,×)进行了对比分析,并在理论分析和实验验证的基础上提出了优先选择乘法算子(+,×)和(∨,×)的建议.
[1] QUINLAN J R. Induction of Decision Trees [J]. Machine Learning 1986, 1(01).
[2] YUFEI YUAN, MICHAEL J SHAW. Induction of fuzzy decision trees [J]. Fuzzy Sets and Systems 1995, 69(02).
[3] UMANO M, OKAMOTO H HATONOI. Fuzzy Decision Trees by Fuzzy ID3 Algorithm and Its Application to Diagnosis System [M]. New York 1994.
[4] YEUNG D S, WANG X Z, TSANG E C C. Learning weighted fuzzy rules from examples with mixed attributes by fuzzy decision trees [A]. 1999.
[5] WANG X Z, YEUNG D S, TSANG E C C. A comparative study on heuristic algorithms for generating furzzy decision trees [J]. IEEE Transactions on Systems Man and Cybernetics-Part B:Cybernetics 2001, 31(02).