The basic idea of KMeans algorithm is that the initial random given K cluster centers, according to the nearest neighbor principle, the sample points are divided into different clusters. Then, the centroid of each cluster is computed by the averaging method, so a new cluster centroid is determined. Iterate until the heart of the cluster moves at a distance less than a given value.

kMeans.py

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