what's the right way to cluster variance why is k mean used for clustering why is k-means algorithm used why is the k-means algorithm used for clustering why is k mean algorithm used what is your cluster? why is it called a k-mean why do clustering algorithms have to minimize variance what is the objective function of this clustering algorithm which cluster algorithm is intended to minimize variance? what is the algorithm that minimizes variance what is the purpose of k-methods algorithm why does k-means algorithm minimize variance? how does k mean cluster variance why is the k m mean algorithm minimizing within cluster variance? why is cluster variance minimized in the k-means algorithm why k means clustering why do you do k mean cluster mean why is k mean algorithm minimizing cluster variance? what is the objective for clustering why is it that the algorithm that has within cluster variance (or is it objective) chooses this as its objective function to minimize?