最短距离算法的聚类对样本进行聚类

样本矩阵 X



输出数据的行数代表了每次聚类后类的个数，每一行的第一个数表示此类样本的个数，

后面的代数表示此类中的样本编号；从程序的输出结果看，聚类的过程一目了然，未聚类

前，有5个类，每个类各有一个样本；第一次聚类是将第一类和第二类合并，得到新的

第一类，此时第一类有2个样本；二第二次聚类是将第3类和第四类合并，得到新的第三类

；第3次聚类是将第2类和第3类合并，此时总共有2类，经过第四次聚类，类的个数变为1，

聚类的过程到此完成。

-　Shortest distance clustering algorithm for clustering the sample matrix X　　Sample rows output data represents the number of classes after each cluster, the first number in each row such that the number of samples,　 behind algebraic expressions such samples in number　output from the program results, the clustering process at a glance, not before clustering　have five classes, each have a sample　clustering is first the first and second categories were combined to give new　first class, this time the first class has two samples　two second cluster is the third and fourth categories were combined to give a new third Class　 3rd clustering is Category 2 and Category 3 merger, this time a total of two classes, after the fourth cluster, into a number of classes,　clustering process is now complete.