sklearn KMeans中的KMeans.cluster_centers_的值 [英] Value at KMeans.cluster_centers_ in sklearn KMeans

问题描述

在进行K表示适合具有3个簇的某些向量时，我能够获得输入数据的标签. KMeans.cluster_centers_返回中心的坐标，因此不应该有一些与之相对应的矢量吗?如何找到这些聚类的质心处的值?

On doing K means fit on some vectors with 3 clusters, I was able to get the labels for the input data. KMeans.cluster_centers_ returns the coordinates of the centers and so shouldn't there be some vector corresponding to that? How can I find the value at the centroid of these clusters?

推荐答案

closest, _ = pairwise_distances_argmin_min(KMeans.cluster_centers_, X)

数组closest将包含X中最接近每个质心的点的索引.

The array closest will contain the index of the point in X that is closest to each centroid.

假设closest给出了三个群集的输出为array([0,8,5]).因此，X [0]是X中最接近质心0的点，X [8]是最接近质心1的点，依此类推.

Let's say the closest gave output as array([0,8,5]) for the three clusters. So X[0] is the closest point in X to centroid 0, and X[8] is the closest to centroid 1 and so on.

来源: https://codedump. io/share/XiME3OAGY5Tm/1/get-nearestpoint-to-centroid-scikit-learn

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