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Entropy weighted k-means (ewkm) by Liping Jing, Michael K. Ng and Joshua Zhexue Huang (2007) doi:10.1109/TKDE.2007.1048 is a weighted subspace clustering algorithm that is well suited to very high dimensional data. Weights are calculated as the importance of a variable with regard to cluster membership. The two-level variable weighting clustering algorithm tw-k-means (twkm) by Xiaojun Chen, Xiaofei Xu, Joshua Zhexue Huang and Yunming Ye (2013) doi:10.1109/TKDE.2011.262 introduces two types of weights, the weights on individual variables and the weights on variable groups, and they are calculated during the clustering process. The feature group weighted k-means (fgkm) by Xiaojun Chen, Yunminng Ye, Xiaofei Xu and Joshua Zhexue Huang (2012) doi:10.1016/j.patcog.2011.06.004 extends this concept by grouping features and weighting the group in addition to weighting individual features.
Citation | wskm citation info |
github.com/SimonYansenZhao/wskm | |
english.siat.cas.cn/ | |
Copyright | 2011-2014 Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences |
Bug report | File report |
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