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# scipy.cluster.hierarchy.fcluster

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

  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]`.
  Returns : | fcluster : ndarray An array of length n. T[i] is the flat cluster number to which original observation i belongs.

### Navigation

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- SciPy v0.9 Reference Guide (DRAFT) »
- Clustering package (`scipy.cluster`) »
- Hierarchical clustering (`scipy.cluster.hierarchy`) »