J unsup is a quadratic function of {µ k }, and it can be minimized by setting its derivative with respect to {µ k } to zero.
then, we can easily solve {µ k } as µ k is equal to the mean of all the data points assigned to cluster k. the classical k-means algorithm only uses unlabeled data, and solves the clustering problem under the unsupervised learning framework.