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文章目錄

• • Clustering by Passing Messages Between Data Points

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Clustering by Passing Messages Between Data Points

通過(guò)在數(shù)據(jù)點(diǎn)之間傳遞消息進(jìn)行聚類(lèi)

Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initial choice is close to a good solution. We devised a method called “affinity propagation,” which takes as input measures of similarity between pairs of data points. Real-valued messages are exchanged between data points until a high-quality set of exemplars and correspondin

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