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

Published: 6 November 2020| Version 1 | DOI: 10.17632/r4wdbpkg99.1
Teng Qiu


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).


Steps to reproduce

Run demo.m.