The main steps in the k-means clustering algorithm are

The main steps in the k-means clustering algorithm are

  •  Assign each sample to the closest centroid, then calculate the new centroid.
  •  Calculate the centroids, then determine the appropriate stopping criterion depending on the number of centroids.
  •  Calculate the distances between the cluster centroids, then find the two closest centroids.
  •  Count the number of samples, then determine the initial centroids.

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