How to implement a sklearn -AgglomerativeClustering from clusters?


How to implement a sklearn -AgglomerativeClustering from clusters?



I'd like to perform a "mixed" unsupervised clustering which uses first a KMeans algorithm to generate a certain number of first small and homogeneous clusters and THEN apply a hierarchical clustering on these clusters I get from Kmeans.



I used cluster.Kmeans from scikit-learn for the first part, and I have my clusters but then I don't know how to use the AgglomerativeClustering function from sklearn so that it can go from those clusters.



Any ideas?



Thank you !





Welcome to SO; please go through the help pages, and be sure to read What topics can I ask about here? and How do I ask a good question?. We are most willing to help, but we cannot do so unless you share what you have tried so far, what exactly is your problem, and what is the desired result...
– desertnaut
Jun 28 at 13:59





1 Answer
1



You also get the labels from KMeans.



These give you the partitions.



Just see the manual.






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