Partitional clustering algorithms focus on dividing the data space into a specific number of partitions or divisions. The main goal is to segment the data into clusters in such a way that objects within a cluster are more similar to each other than to objects in other clusters.
[[K-means]] is a well-known example of a partitional clustering algorithm.
Spectral
Hierarchical
Me: "How do I pick a clustering algorithm when n_observations is unknown??"
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