fuzzy C-means clustering 均值聚类 ; 模糊c均值聚类 ; 聚类
Fuzzy C-Means Clustering Algorithm 模糊C均值聚类算法 ; 模糊C ; 均值聚类方法 ; 法
hybrid c-means clustering 混合c均值聚类
possibilistic C-means clustering 可能性C均值聚类
fast fuzzy c-means clustering 快速模糊c均值聚类
Weighted fuzzy C-means clustering 加权模糊C
A new weighted hybrid C-means clustering based on the K-nearest-neighbour rule is presented in this paper.
该文提出了一种基于K近邻加权的混合C均值聚类算法。
Firstly, the advantages of fuzzy C-means clustering and possibilistic C-means clustering are utilized in this paper.
首先该文利用模糊C均值聚类和可能性C均值聚类的优点，设计出一种混合C均值聚类算法。
The classical C-means clustering algorithm (CMA) is a well-known clustering method to partition an image into homogeneous regions.
经典的C -均值聚类算法（CMA）是将图像分割成C类的常用方法，但依赖于初始聚类中心的选择。
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