% U: C×N 型矩阵,FCM 的划分矩阵 % P: C×S 型矩阵,FCM 的聚类中心,每一行对应一个聚类原型 % Dist: C×N 型矩阵,FCM 各聚类中心到各样本点的距离,聚类中 %心 i 到样本点 j 的距离为 Dist(i,j) % Cluster_Res: 聚类结果,共 C 行,每一行对应一类 % Obj_Fcn: 目标函数值 % iter: FCM ...
k均值聚类 k均值聚类的实现中,把每个样本划分到单一的类别中,亦即是每个样本只能属于一种类别,不能属于多种类别。这样的划分,称为硬划分。 模糊c均值均类 为了解决硬划分所带来的问题,因此有了称为软划分的聚类算法,这一类算法中,每个样本不再只能属于一种类别,而是对于每个样本,都有对应的隶属度数组,数组里的每...
Fuzzy C-Means算法是一种基于模糊集合理论的聚类方法，不同于K-Means算法中只将每个数据点归为一个簇...
(c– 1). Then, each itemxiof the finite setXhas the flexibility of mapping to one or more clusters. Hence, a membership or affinity score is introduced here,uij, which is for itemxiwith respect toCj. This type of clustering is calledsoft clustering. Since it brings in an element of ...
FCM(Fuzzy c-means)算法的基本过程: 假设需要将数据集中的数据分为C种类型,那么就存在C个聚类中心,每个数据样本i属于某一类型的隶属度(概率)为$\mu_ij$,因此目标函数可以写成$J = \sum^C_{i=1}\sum^n_{j=1}\mu^m_{ij}(x_j-C_i)^2$(当样本靠近其隶属的类型中心点时,其距离小,概率大,反之距...
Biswal B, Dash PK, Panigrahi BK (2009) Power quality disturbance classification using fuzzy C-means algorithm and adaptive particle swarm optimization. IEEE Trans Ind Electron 56(1):212–220 Article Google Scholar Brandeau ML, Chiu SS (1989) An overview of representative problems in location re...
The fuzzy c-means algorithm (Algorithm 12.6) is similar to the crisp k-means algorithm (Algorithm 12.4). It minimizes the intra-cluster variance, but has the same problems as the k-means: it may get stuck in a local minimum, and its results depend on the initial choice of cluster center...
Fuzzy c-means (FCM) algorithm is one o... H Izakian,A Abraham,V Snásel - IEEE 被引量: 85发表: 2010年 A multi-objective genetic algorithm with fuzzy c-means for automatic data clustering This article presents a multi-objective genetic algorithm which considers the problem of data ...
Fuzzy C-means clustering of incomplete data , where the second and fifth feature values are missing. The fuzzy c-means (FCM) algorithm is a useful tool for clustering real s-dimensional data, but it ... RJ Hathaway,JC Bezdek - 《Systems Man & Cybernetics Part B Cybernetics IEEE ...