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Influence of T-norm and T-conorm operators in Fuzzy ID3 algorithm

机译:T-NARM和T-Conorm运算符在模糊ID3算法中的影响

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Fuzzy ID3 algorithm is a widely studied classification algorithm in order to induce fuzzy decision trees. The structure of fuzzy decision trees combines the interpretability of the decision trees with the capability of fuzzy logic on uncertainty. The fuzzy inference procedure of fuzzy decision trees is a crucial manner for the classification problems. So, the choice of the aggregation operators for the inference procedure is very important. The aim of this study is to view the performance of Fuzzy inference procedure of Fuzzy ID3 algorithm within different triangular norm (T-norm) and triangular conorm (T-conorm) operators. The fuzzy inference procedure was applied by using four different T-norm and T-conorm operators (Zadeh, Product-Sum_Umano, Yager and Hamacher). These operators were applied within the fuzzy inference phase of the system. Fuzzy c-means clustering algorithm (FCM) was used for the fuzzification of datasets. After the pre-fuzzification process, Fuzzy ID3 algorithm was performed on seven numerical datasets (Appendicitis, Balance, Iris, Wine, Hearth, New Thyroid, Haberman) selected from the KEEL data set repository. The study was encouraged with the statistical tests. The hypothesis validation techniques were used. In future studies, it is expected that by using different parameters for parametrized operators, the best accuracy rates can be handled.
机译:模糊ID3算法是一种广泛研究的分类算法,以诱导模糊决策树。模糊决策树的结构结合了决策树的可解释性与不确定的模糊逻辑能力。模糊决策树的模糊推理程序是对分类问题的关键方式。因此,推理程序的聚合运算符的选择非常重要。本研究的目的是在不同三角标准(T-NORM)和三角形(T-Conorm)运算符中的模糊ID3算法模糊推理程序的性能。使用四种不同的T-NORM和T-Conorm运算符(Zadeh,Product-Sum_umano,Yager和Hamacher)应用模糊推理程序。这些运营商应用于系统的模糊推理阶段。模糊C-Means聚类算法(FCM)用于数据集的模糊化。在预先模糊化过程之后,在从龙骨数据集存储库中选择的七个数值数据集(阑尾炎,平衡,虹膜,葡萄酒,壁炉,新的甲状腺,Haberman)进行模糊ID3算法。统计测试鼓励研究。使用假设验证技术。在未来的研究中,预期通过使用对参数化运营商的不同参数,可以处理最佳的准确率。

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