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Algorithms for clustering large datasets in arbitrary metric spaces

Algorithms for clustering large datasets in arbitrary metric spaces. A set of 2-dimensional points shown adjacent. They clearly form three distinct groups (called clusters ). The goal of any clustering algorithm is to find such groups in data to better understand its distribution.

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388 views • 27 slides

BIRCH: An Efficient Data Clustering Method for Very Large Databases

BIRCH: An Efficient Data Clustering Method for Very Large Databases. Tian Zhang, Raghu Ramakrishnan, Miron Livny University of Wisconsin-Maciison Presented by Zhirong Tao. Outline of the Paper. Background Clustering Feature and CF Tree The BIRCH Clustering Algorithm Performance Studies.

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517 views • 15 slides

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Algorithms for clustering large datasets in arbitrary metric spaces

BIRCH: An Efficient Data Clustering Method for Very Large Databases