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Published November 21, 2023 | Version v1.0.9
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CLASSIX: v1.0.9

Authors/Creators

  • 1. The University of Manchester

Description

CLASSIX is a fast and explainable clustering method. It consists of two phases, namely a greedy aggregation phase of the sorted data into groups of nearby data points,  followed by the merging of groups into clusters. The algorithm is controlled by two scalar parameters, namely a distance parameter for the aggregation and another parameter controlling the minimal cluster size. Its inherent simplicity allows for the generation of intuitive explanations of the computed clusters.

Files

classix.zip

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Additional details

Dates

Copyrighted
2023-11-21
CLASSIX is a fast and explainable clustering method. It consists of two phases, namely a greedy aggregation phase of the sorted data into groups of nearby data points, followed by the merging of groups into clusters. The algorithm is controlled by two scalar parameters, namely a distance parameter for the aggregation and another parameter controlling the minimal cluster size. Its inherent simplicity allows for the generation of intuitive explanations of the computed clusters.

References

  • X. Chen and S. Güttel. Fast and explainable sorted based clustering, 2022