获取最接近数据的索引指向MATLAB中Kmeans聚类中的中心点

Question

我在MATLAB中使用K-means进行一些聚类.您可能知道用法如下:

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

其中IDX给出X中每个数据点的簇号,C给出每个簇的质心.我需要得到距离质心最近的数据点的索引(实际数据集X中的行号).有谁知道我怎么做到这一点？谢谢

Answer 1

@Dima提到的"蛮力方法" 如下

%# loop through all clusters
for iCluster = 1:max(IDX)
    %# find the points that are part of the current cluster
    currentPointIdx = find(IDX==iCluster);
    %# find the index (among points in the cluster)
    %# of the point that has the smallest Euclidean distance from the centroid
    %# bsxfun subtracts coordinates, then you sum the squares of
    %# the distance vectors, then you take the minimum
    [~,minIdx] = min(sum(bsxfun(@minus,X(currentPointIdx,:),C(iCluster,:)).^2,2));
    %# store the index into X (among all the points)
    closestIdx(iCluster) = currentPointIdx(minIdx);
end

要获取最接近群集中心的点的坐标k,请使用

X(closestIdx(k),:)