macroclusters
Macroclusters are large-scale groupings of data points created by aggregating smaller, densely packed subgroups known as microclusters into a higher-level partition. In clustering analysis, macroclusters help summarize complex datasets by revealing broad structure while suppressing fine-grained detail. They are particularly relevant in multi-scale or hierarchical clustering workflows, where patterns are sought at different levels of granularity.
Macroclusters can be formed through several approaches. One common method is hierarchical clustering with a coarse
Applications span diverse domains. In image analysis, macroclusters may represent regions of interest larger than fine
Evaluating macroclusters involves internal validity indices, stability assessments, and domain validation. Challenges include choosing an appropriate