Machine Learning #74 CURE Algorithm | Clustering
In this lecture of macghine learning we are going to see CURE Algorithm for clustering with example. A new scalable algorithm called CURE is introduced, which uses random sampling and partitioning to reliably find clusters of arbitrary shape and size. CURE algorithm clusters a random sample of the database in an agglomerative fashion, dynamically updating a constant number c of well-scattered points. CURE divides the random sample into partitions which are pre-clustered independently, then the partially-clustered sample is clustered further by the agglomerative algorithm. A new algorithm for detecting arbitrarily-shaped clusters at large-scale is presented and named CURE, for “Clustering Using Representatives”.
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