CLARANS

CLARANS (Clustering Large Applications based upon RANdomized Search) is an algorithm used to group similar data points into clusters, especially with large datasets. Unlike traditional methods that examine all possible groupings, CLARANS uses a randomized approach to efficiently explore potential cluster configurations. It repeatedly selects random samples of data points as potential centers (medoids) and evaluates how well they form cohesive groups. This process helps find good local solutions faster, making it suitable for large, complex data. In essence, CLARANS balances accuracy and efficiency to identify meaningful patterns within extensive datasets.