Agglomerative Clustering

Agglomerative clustering is a hierarchical clustering method that builds nested clusters by merging smaller clusters into larger ones. It starts with each data point as its own cluster and iteratively combines the closest pairs of clusters based on a distance metric until a specified number of clusters is reached or all points are merged into a single cluster. This method is characterized by its bottom-up approach and can be visualized using dendrograms, which illustrate the merging process. Common use cases include market segmentation, social network analysis, and image segmentation, where understanding the structure of data is crucial.