Clustered

Clustered is the past participle of cluster and an adjective used to describe objects, people, or events arranged or grouped together in a cluster or multiple clusters. It implies proximity or association but not necessarily precise or uniform arrangement. Examples: leaves clustered at the stem, houses clustered around a village square, or data points clustered in a scatter plot.

In data analysis, clustering refers to unsupervised learning methods that partition a set of observations into groups, or clusters, such that members within a cluster are more similar to each other than to those in other clusters. When data are described as clustered, they exhibit within-cluster similarity and between-cluster dissimilarity. Algorithms include k-means, hierarchical clustering, and density-based methods. In econometrics and statistics, clustered data require special variance estimation, such as cluster-robust standard errors, to account for correlations within the same cluster.

In databases, a clustered index determines the physical order of rows in a table. A table can have at most one clustered index, and non-clustered indexes point to the data rows. The term "clustered" describes this arrangement and can affect performance for range queries and updates.

In astronomy, star clusters are gravitationally bound groups of stars; objects in a region described as clustered are more densely packed than average. In urban planning or ecology, "clustered" can describe distributions of facilities, habitats, or populations that occur in localized pockets rather than evenly across an area.

Historically, the term derives from cluster, with the suffix -ed marking completed state or description.