Editing Central tendency (section)

===Clustering===
Instead of a single central point, one can ask for multiple points such that the variation from these points is minimized. This leads to [[cluster analysis]], where each point in the data set is clustered with the nearest "center". Most commonly, using the 2-norm generalizes the mean to [[k-means clustering|''k''-means clustering]], while using the 1-norm generalizes the (geometric) median to [[k-medians clustering|''k''-medians clustering]]. Using the 0-norm simply generalizes the mode (most common value) to using the ''k'' most common values as centers.

Unlike the single-center statistics, this multi-center clustering cannot in general be computed in a [[closed-form expression]], and instead must be computed or approximated by an [[iterative method]]; one general approach is [[expectation–maximization algorithm]]s.