kmeans
K-means clustering

Syntax

IDX = kmeans(X,k)
[IDX,C] = kmeans(X,k)
[IDX,C,sumd] = kmeans(X,k)
[IDX,C,sumd,D] = kmeans(X,k)
[...] = kmeans(...,param1,val1,param2,val2,...)

Description

IDX = kmeans(X,k) partitions the points in the n-by-p data matrix X into k clusters. This iterative partitioning minimizes the sum, over all clusters, of the within-cluster sums of point-to-cluster-centroid distances. Rows of X correspond to points, columns correspond to variables. kmeans returns an n-by-1 vector IDX containing the cluster indices of each point. By default, kmeans uses squared Euclidean distances.

2楼: Originally posted by libralibra at 2012-07-06 19:13:54
kmeans不用下啊,matlab内置的有

kmeans
K-means clustering

Syntax

IDX = kmeans(X,k)
= kmeans(X,k)
= kmeans(X,k)
= kmeans(X,k)
= kmeans(...,param1,val1,param2,val2,...)

Description ...