Agglomerative vs. Divisive Clustering
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Agnes/Diana
Agglomerative Nesting (Hierarchical Clustering)
DIvisive ANAlysis Clustering
Agglomerative Clustering:
(Leaves to trunk)
We start out with all sample units in n clusters of size 1.
Then, at each step of the algorithm, the pair of clusters with the shortest distance are combined into a single cluster.
The algorithm stops when all sample units are combined into a single cluster of size n.
Divisive Clustering:
(Trunk to leaves)
We start out with all sample units in a single cluster of size n.
Then, at each step of the algorithm, clusters are partitioned into a pair of daughter clusters, selected to maximize the distance between each daughter.
The algorithm stops when sample units are partitioned into n clusters of size 1.
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