wskm

Weighted k-Means Clustering

CRAN Package

Entropy weighted k-means (ewkm) by Liping Jing, Michael K. Ng and Joshua Zhexue Huang (2007) 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) 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) extends this concept by grouping features and weighting the group in addition to weighting individual features.


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  • Depends5 packages