Interpretable clustering: an optimization approach
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DOI: 10.1007/s10994-020-05896-2
Abstract: State-of-the-art clustering algorithms provide little insight into the rationale for cluster membership, limiting their interpretability. In complex real-world applications, the latter poses a barrier to machine learning adoption when experts are asked to provide detailed… read more here.
Keywords: optimization approach; interpretable clustering; optimization; clustering optimization ... See more keywords