You should be able to define initial centroids #11
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Fixed |
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Actually this is not fixed. It is still a valid issue. Now you have the posibility of defining the initial centroids. But when initializing the centroids if taking those centroids as the best one possibles of the moment. See The expected behavior of this issue is to initialize the initial centroids and then starting to run the algo from those centroids. Not to take those centroids as the best ones possible. |
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When initializating kmeans, you should be able to choose if you want the initial centroids to be random or #6, or if you want to set your own initial centroids. Keep in mind that If an array is passed, it should be of shape (n_clusters, n_features) and gives the initial centers or else raise an exception.
https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html.
Adding this feature would be helpful in testing that empty clusters are relocated as expected if you give one initial centroid that is far from the data which means that a cluster will be empty on the first iteration
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