Machine Learning, Data Science, Clustering, Classification, Algorithms.
somewhere around (-1, -1) and (1, 1). Update First, based on those k-initialization points, we would need to identify which data points are close to each k-initialization points. We would have something like boundary line in the picture on the middle. After that, we move those k-points to the