在 MATLAB 中查询 k-means 聚类 [英] Query regarding k-means clustering in MATLAB

问题描述

我有大量矩阵形式的数据.我已经在 MATLAB R2013a 中使用 k 均值聚类对其进行了聚类.我想要形成的每个簇的质心的确切坐标..是否可以使用任何公式或其他任何东西?

I have a very large amount of data in the form of matrix.I have already clustered it using k-means clustering in MATLAB R2013a. I want the exact coordinates of the centroid of each cluster formed.. Is it possible using any formula or anything else?

我想找出每个簇的质心，这样每当有新数据到达矩阵时，我就可以计算它与每个质心的距离，从而找出新数据所属的簇

I want to find out the centroid of each cluster so that whenever some new data arrives in matrix, i can compute its distance from each centroid so as to find out the cluster to which new data will belong

我的数据本质上是异构的.所以，很难找出每个集群的数据的平均值.所以，我正在尝试编写一些代码来自动打印质心位置.

My data is heterogeneous in nature.So,its difficult to find out average of data of each cluster.So, i am trying to write some code for printing the centroid location automatically.

推荐答案

在 MATLAB 中，使用

In MATLAB, use

[idx,C] = kmeans(..) 

代替

idx = kmeans(..) 

根据文档:

[idx,C] = kmeans(..) 返回 k×p 矩阵 C 中的 k 个簇质心位置.

[idx,C] = kmeans(..) returns the k cluster centroid locations in the k-by-p matrix C.

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