BIRCH Clustering

BIRCH was developed to support memory-efficient and incremental clustering, especially on large datasets. By summarizing data into clustering-feature trees, it reduces the need to operate directly on every point. This makes it attractive for streaming-like or large-scale scenarios. However, final clustering quality depends on the structure’s parameters and the underlying topology of the data.