【摘要】 模糊c-均值(FCM)聚类算法是一种通过目标函数的极小化来获得数据集模糊划分的方法。其中,模糊加权指数m对FCM算法的分类性能有着重要的影响,而调用FCM算法进行模糊聚类分析时又必须给m赋值。因此,模糊加权指数m的优选研究就变得很有意义。基于模糊决策的方法本文给出了一种对m的优选方法,实验结果表明该方法是有效的更多还原

【Abstract】 Fuzzy c-mean(FCM) is a popular and effective algorithm for obtaining an optimal fuzzy (partition) of data set by minimizing an objective function, in which the weighting exponent m plays an important role. To perform the FCM algorithm, a proper value should be assigned to the parameter m. It thus is essential for us to study the optimal choice of m. For this end, this paper presents an (optimal) choice method for m based on fuzzy decision theory. The experimental results illustrate the (effectiveness) of the proposed method.更多还原