scipy.cluster.hierarchy.ward

scipy.cluster.hierarchy.ward(y)

Performs Ward’s linkage on a condensed distance matrix.

See linkage for more information on the return structure and algorithm.

The following are common calling conventions:

1. Z = ward(y) Performs Ward’s linkage on the condensed distance matrix y.
2. Z = ward(X) Performs Ward’s linkage on the observation matrix X using Euclidean distance as the distance metric.

Parameters:

y : ndarray

A condensed distance matrix. A condensed distance matrix is a flat array containing the upper triangular of the distance matrix. This is the form that pdist returns. Alternatively, a collection of m observation vectors in n dimensions may be passed as a m by n array.

Returns:

Z : ndarray

The hierarchical clustering encoded as a linkage matrix. See linkage for more information on the return structure and algorithm.

See also

linkage

for advanced creation of hierarchical clusterings.

scipy.spatial.distance.pdist

pairwise distance metrics