Construct and visualize the hierarchical cluster of arbitrary data using the new
ClusteringTree
function in Version 11.
Cluster cities based on the proximity to one another:
In[291]:=
ClusteringTree
London
CITY
,
Paris
CITY
,
Chicago
CITY
,
Tokyo
CITY
,
Boston
CITY
,
Moscow
CITY
,
San Diego
CITY
,
Baltimore
CITY

Out[291]=
Obtain a cluster hierarchy from a list of colors:
In[151]:=
colors=RandomColor[18]
Out[151]=

,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,

In[152]:=
ClusteringTree[colors,ClusterDissimilarityFunction"Centroid"]
Out[152]=
Choose a different
GraphLayout
:
In[117]:=
ClusteringTree[RandomColor[40],ClusterDissimilarityFunction"Centroid",GraphLayout"RadialDrawing"]
Out[117]=