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What are some of the possible linkage types to use in order to form successive clusters?

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  • Ward: The Ward linkage forms successive clusters by finding the clusters that minimize the increase in within-cluster variance at each step. It is the default option in sklearn’s hierarchical clustering API. 
  • Single: The next cluster is formed by merging the observation that has the shortest minimum distance to an existing cluster. 
  • Complete: The next cluster is formed by merging the observation that has the shortest maximum distance to an existing cluster. 
  • Average: The next cluster is formed by merging the observation with the shortest average distance to an existing cluster. 

Note: In divisive clustering, clusters are formed by dividing existing clusters that maximize the choice of linkage, essentially working inversely to what was described for each option. 

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