How to implement Hierarchical Clustering in shogun
In this recipe, we shall learn how to implement Hierarchical Clustering in shogun. We shall do so with the help of a simple example.
Recipe Objective: How to implement Hierarchical Clustering in shogun?
This recipe explains how to implement Hierarchical Clustering in shogun.
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Hierarchical Clustering
We use Hierarchical clustering to build a hierarchy of clusters to achieve such a bottom-up approach in which its cluster starts every observation. It follows a greedy manner; initially, the pairwise distance matrix is constructed, and then, the clusters of the pair with the closest distance are merged iteratively.
x_train = RealFeatures(f_train)
d = EuclideanDistance(x_train, x_train)
h = Hierarchical(3, d)
d = h.get_merge_distances()
cp = h.get_cluster_pairs()
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I come from Northwestern University, which is ranked 9th in the US. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge.... Read More