scipy.cluster.hierarchy.fcluster¶

scipy.cluster.hierarchy.fcluster(Z, t, criterion='inconsistent', depth=2, R=None, monocrit=None)[source]

Forms flat clusters from the hierarchical clustering defined by the linkage matrix Z.

Parameters: Z : ndarray The hierarchical clustering encoded with the matrix returned by the linkage function. t : float The threshold to apply when forming flat clusters. criterion : str, optional The criterion to use in forming flat clusters. This can be any of the following values: inconsistent : If a cluster node and all its descendants have an inconsistent value less than or equal to t then all its leaf descendants belong to the same flat cluster. When no non-singleton cluster meets this criterion, every node is assigned to its own cluster. (Default) distance : Forms flat clusters so that the original observations in each flat cluster have no greater a cophenetic distance than t. maxclust : Finds a minimum threshold r so that the cophenetic distance between any two original observations in the same flat cluster is no more than r and no more than t flat clusters are formed. monocrit : Forms a flat cluster from a cluster node c with index i when monocrit[j] <= t. For example, to threshold on the maximum mean distance as computed in the inconsistency matrix R with a threshold of 0.8 do: MR = maxRstat(Z, R, 3) cluster(Z, t=0.8, criterion='monocrit', monocrit=MR)  maxclust_monocrit : Forms a flat cluster from a non-singleton cluster node c when monocrit[i] <= r for all cluster indices i below and including c. r is minimized such that no more than t flat clusters are formed. monocrit must be monotonic. For example, to minimize the threshold t on maximum inconsistency values so that no more than 3 flat clusters are formed, do: MI = maxinconsts(Z, R) cluster(Z, t=3, criterion='maxclust_monocrit', monocrit=MI)  depth : int, optional The maximum depth to perform the inconsistency calculation. It has no meaning for the other criteria. Default is 2. R : ndarray, optional The inconsistency matrix to use for the ‘inconsistent’ criterion. This matrix is computed if not provided. monocrit : ndarray, optional An array of length n-1. monocrit[i] is the statistics upon which non-singleton i is thresholded. The monocrit vector must be monotonic, i.e. given a node c with index i, for all node indices j corresponding to nodes below c, monocrit[i] >= monocrit[j]. fcluster : ndarray An array of length n. T[i] is the flat cluster number to which original observation i belongs.