The Ward algorithm is a commonly-used hierarchical variance-minimization al
The Ward algorithm is a commonly-used hierarchical variance-minimization algorithm of this type. An  algorithm of this type whose time complexity is quadratic in number of samples and linear in number of  iterations sends messages between data points until convergence; that algorithm, which relies on  whether a given point can be an exemplar for another point is cal ed affinity propagation. One algorithm  of this type relies on defining core samples and a minimum distance between samples in order to isolate  high-density regions; that algorithm is cal ed DBSCAN. Another algorithm of this type minimizes a  "distortion measure" by reassigning the labels of the data points and recomputing the means, leading it  to be known as the "K-means" algorithm for this process. For 10 points, identify this type of algorithm  which groups data points together in a multidimensional space based on common features.
The Ward algorithm is a commonly-used hierarchical variance-minimization algorithm of this type.
clustering algorithm