I'm trying to build a dendrogram using the children_
attribute provided by AgglomerativeClustering
, but so far I'm out of luck. I can't use scipy.cluster
since agglomerative clustering provided in scipy
lacks some options that are important to me (such as the option to specify the amount of clusters). I would be really grateful for a any advice out there.
import sklearn.cluster
clstr = cluster.AgglomerativeClustering(n_clusters=2)
clusterer.children_
Here is a simple function for taking a hierarchical clustering model from sklearn and plotting it using the scipy dendrogram
function. Seems like graphing functions are often not directly supported in sklearn. You can find an interesting discussion of that related to the pull request for this plot_dendrogram
code snippet here.
I'd clarify that the use case you describe (defining number of clusters) is available in scipy: after you've performed the hierarchical clustering using scipy's linkage
you can cut the hierarchy to whatever number of clusters you want using fcluster
with number of clusters specified in the t
argument and criterion='maxclust'
argument.