Divisive

Divisive refers to a clustering algorithm that recursively divides data into smaller subsets based on a chosen criterion until each subset consists of only one data point. The algorithm starts with the entire dataset and splits it into two or more subsets based on the feature that maximizes the difference between the subsets. This process is repeated on each subset until a stopping criterion is met, such as a minimum subset size or a maximum number of iterations. Divisive clustering is a top-down approach that can handle large datasets and non-convex clusters. However, it is sensitive to the initial partition and the choice of the splitting criterion, which can lead to suboptimal results.

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Divisive

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