FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。在介绍FCM具体算法之前我们先介绍一些模糊集合的基本知识。(The FCM algorithm is a partition-based clustering algorithm. Its idea is to make the similarity among the objects that are divided into the same cluster be the largest, and the similarity between different clusters is the smallest. The fuzzy C-means algorithm is an improvement of the ordinary C-means algorithm. The common C-means algorithm is hard for the data division, and FCM is a flexible fuzzy division. Before introducing the specific FCM algorithm, we first introduce some basic knowledge of fuzzy sets.)