Matlab实现k-means聚类算法

k-means是聚类中的一个十分经典的算法，具体的思想可以参考Andrew Ng的讲义《The k-means clustering algorithm》，这里不再赘述。

 

需要用到Matlab中的核心函数kmeans，具体用法可以参考Matlab命令: doc kmeans

IDX = kmeans(X,k)

[IDX,C] = kmeans(X,k)

[IDX,C,sumd] = kmeans(X,k)

[IDX,C,sumd,D] = kmeans(X,k)

partitions the points in the n-by-p data matrix X into k clusters.  Rows of X correspond to points, columns correspond to variables. 

n-by-1 vector IDX containing the cluster indices of each point. 

k cluster centroid locations in the k-by-p matrix C.

within-cluster sums of point-to-centroid distances in the 1-by-k vector sumd.

distances from each point to every centroid in the n-by-k matrix D.

还有一些可选的参数，包括：'distance', 'options', 'replicates'等。

'distance'表示距离，缺省为欧几里得距离，还包括绝对距离，cos距离，海明距离等。

'options'可以通过sta