遇见数据集

Data for: Enhancing In-Tree-based Clustering via Distance Ensemble and Kernelization

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NIAID Data Ecosystem2026-03-12 收录
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Run demo.m. This can reproduce the results in Fig.4A for the following TWO clustering methods on 30 test datasets. 1) ND-Ward-E(KT): the proposed clustering method published in Pattern Recognition in 2020 (Title: "Enhancing In-Tree-based Clustering via Distance Ensemble and Kernelization" by Teng Qiu and Yongjie Li) 2) ND-K: a compared method (Qiu, et al. "Nearest descent, in-tree, and clustering",arXiv:1412.5902v2, 2014.) Note: for ND.m, function "maxk" may not exist in low-version Matlab; in this case, the following code behind it in ND.m can be used instead (we have highlighted it in ND.m).

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2020-11-06
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