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10.3. Bisecting k-means

To overcome the problem of poor clusters because of k-means getting caught in a local minimum, another algorithm has been developed. This algorithm, known as bisecting k-means, starts out with one cluster and then splits the cluster in two. It then chooses a cluster to split. The cluster to split is decided by minimizing the SSE. This splitting based on the SSE is repeated until the user-defined number of clusters is attained.

Pseudocode for bisecting k-means will look like this:


  

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