DCLUSTF Dissimilarity based clustering by the FFT algorithm.
LAB = DCLUSTF(D,K)
DescriptionThe FFT (Farthest First Traversal) algorithm is used to find a set of K prototypes. All other objects are assigned to the nearest prototype. In LAB for all objects the index in D of the nearest cluster prototype is returned. If K is a vector LAB has length(K) columns, returning a multilevel clustering. Note that the FFT algorithm is not really a clustering procedure but just a fast way to split the data in spatially distant parts. Clusterings can be evaluated by CLUSTEVAL, CLUSTCERR or CLUSTC on the basis of (some) true labels. See alsodatasets, mappings, kmeans, prkmeans, clustk, dclustm, dclusth, dcluste, clusteval, clustcerr, clustc,
