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arXiv · 1108.0017

Generating a Diverse Set of High-Quality Clusterings

Jeff M. Phillips·Parasaran Raman·Suresh Venkatasubramanian
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Abstract

We provide a new framework for generating multiple good quality partitions (clusterings) of a single data set. Our approach decomposes this problem into two components, generating many high-quality partitions, and then grouping these partitions to obtain k representatives. The decomposition makes the approach extremely modular and allows us to optimize various criteria that control the choice of representative partitions.

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Jeff M. Phillips, Parasaran Raman, Suresh Venkatasubramanian. 2011-07-29. Generating a Diverse Set of High-Quality Clusterings. https://arxiv.org/abs/1108.0017

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