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This Python package provides an implementation of a clustering algorithm for finding compact clusters in high-dimensional descriptor spaces.

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kubanmar/similarity_threshold_clusterer

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This Python package provides a clustering method for finding small compact clusters in a high dimensional descriptor space.

The algorithm implemented in this package is introduced, explained, and used in Ref. [1].

[1] Kuban, M., Rigamonti, S., Scheidgen, M, and Draxl, C.. Density-of-states similarity descriptor for unsupervised learning from materials data. Sci Data 9, 646 (2022). https://doi.org/10.1038/s41597-022-01754-z

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This Python package provides an implementation of a clustering algorithm for finding compact clusters in high-dimensional descriptor spaces.

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