Generating a Diverse Set of High-Quality Clusterings
CoRR(2011)
摘要
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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关键词
diverse set,high-quality high-quality
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