说明：  用K均值算法和C模糊算法对sonar数据和iris数据进行分类。 K均值算法是一种很常用的聚类算法，其基本思想是，通过迭代寻找K个聚类的一种划分方法，使得用这K个聚类的均值来代表各类样本是所得到的的总体误差最小。 模糊C均值（FCM）算法在K均值算法的基础上，用模糊子集代替确定子集，从而得到模糊的分类结果，即分类结果的模糊化。
(Sonar data and iris data are classified by means of K mean algorithm and C fuzzy algorithm. The K mean algorithm is a very common clustering algorithm. Its basic idea is to find a partition method of K clustering by iteration, so that the average error of the mean of the K clustering is minimized. The fuzzy C mean (FCM) algorithm is based on the K mean algorithm. The fuzzy subset is replaced by the fuzzy subset, thus the fuzzy classification result is obtained, that is, the classification result is fuzzed.)