Hierarchical clustering (scipy.cluster.hierarchy
)¶
These functions cut hierarchical clusterings into flat clusterings or find the roots of the forest formed by a cut by providing the flat cluster ids of each observation.
fcluster (Z, t[, criterion, depth, R, monocrit]) |
Form flat clusters from the hierarchical clustering defined by the given linkage matrix. |
fclusterdata (X, t[, criterion, metric, …]) |
Cluster observation data using a given metric. |
leaders (Z, T) |
Return the root nodes in a hierarchical clustering. |
These are routines for agglomerative clustering.
linkage (y[, method, metric, optimal_ordering]) |
Perform hierarchical/agglomerative clustering. |
single (y) |
Perform single/min/nearest linkage on the condensed distance matrix y . |
complete (y) |
Perform complete/max/farthest point linkage on a condensed distance matrix. |
average (y) |
Perform average/UPGMA linkage on a condensed distance matrix. |
weighted (y) |
Perform weighted/WPGMA linkage on the condensed distance matrix. |
centroid (y) |
Perform centroid/UPGMC linkage. |
median (y) |
Perform median/WPGMC linkage. |
ward (y) |
Perform Ward’s linkage on a condensed distance matrix. |
These routines compute statistics on hierarchies.
cophenet (Z[, Y]) |
Calculate the cophenetic distances between each observation in the hierarchical clustering defined by the linkage Z . |
from_mlab_linkage (Z) |
Convert a linkage matrix generated by MATLAB(TM) to a new linkage matrix compatible with this module. |
inconsistent (Z[, d]) |
Calculate inconsistency statistics on a linkage matrix. |
maxinconsts (Z, R) |
Return the maximum inconsistency coefficient for each non-singleton cluster and its children. |
maxdists (Z) |
Return the maximum distance between any non-singleton cluster. |
maxRstat (Z, R, i) |
Return the maximum statistic for each non-singleton cluster and its children. |
to_mlab_linkage (Z) |
Convert a linkage matrix to a MATLAB(TM) compatible one. |
Routines for visualizing flat clusters.
dendrogram (Z[, p, truncate_mode, …]) |
Plot the hierarchical clustering as a dendrogram. |
These are data structures and routines for representing hierarchies as tree objects.
ClusterNode (id[, left, right, dist, count]) |
A tree node class for representing a cluster. |
leaves_list (Z) |
Return a list of leaf node ids. |
to_tree (Z[, rd]) |
Convert a linkage matrix into an easy-to-use tree object. |
cut_tree (Z[, n_clusters, height]) |
Given a linkage matrix Z, return the cut tree. |
optimal_leaf_ordering (Z, y[, metric]) |
Given a linkage matrix Z and distance, reorder the cut tree. |
These are predicates for checking the validity of linkage and inconsistency matrices as well as for checking isomorphism of two flat cluster assignments.
is_valid_im (R[, warning, throw, name]) |
Return True if the inconsistency matrix passed is valid. |
is_valid_linkage (Z[, warning, throw, name]) |
Check the validity of a linkage matrix. |
is_isomorphic (T1, T2) |
Determine if two different cluster assignments are equivalent. |
is_monotonic (Z) |
Return True if the linkage passed is monotonic. |
correspond (Z, Y) |
Check for correspondence between linkage and condensed distance matrices. |
num_obs_linkage (Z) |
Return the number of original observations of the linkage matrix passed. |
Utility routines for plotting:
set_link_color_palette (palette) |
Set list of matplotlib color codes for use by dendrogram. |