Agglomerative


Agglomerative is a hierarchical clustering algorithm in data science that starts with each data point as a separate cluster and then merges the closest pairs of clusters until a stopping criterion is met. The stopping criterion can be a fixed number of clusters or a threshold distance between clusters. Agglomerative clustering is a bottom-up approach that can be used for exploratory data analysis, pattern recognition, and image segmentation. It is a popular clustering algorithm due to its simplicity and flexibility. However, it can be computationally expensive for large datasets.


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