How to interpret the sample_weight parameter in MiniBatchKMeans?
Yes, the parameter is available in the vanilla K-Means too.

The algorithm supports sample weights, which can be given by a parameter sample_weight. This allows assigning more weight to some samples when computing cluster centers and values of inertia. For example, assigning a weight of 2 to a sample is equivalent to adding a duplicate of that sample to the dataset X.

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