wskm: Weighted k-Means Clustering
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.
| Version: |
1.4.40 |
| Depends: |
R (≥ 2.10), grDevices, stats, lattice, latticeExtra, fpc |
| Published: |
2020-04-05 |
| DOI: |
10.32614/CRAN.package.wskm |
| Author: |
Graham Williams [aut],
Joshua Z Huang [aut],
Xiaojun Chen [aut],
Qiang Wang [aut],
Longfei Xiao [aut],
He Zhao [cre] |
| Maintainer: |
He Zhao <Simon.Yansen.Zhao at gmail.com> |
| BugReports: |
https://github.com/SimonYansenZhao/wskm/issues |
| License: |
GPL (≥ 3) |
| Copyright: |
2011-2014 Shenzhen Institutes of Advanced Technology Chinese
Academy of Sciences |
| URL: |
https://github.com/SimonYansenZhao/wskm,
http://english.siat.cas.cn/ |
| NeedsCompilation: |
yes |
| Citation: |
wskm citation info |
| Materials: |
ChangeLog |
| CRAN checks: |
wskm results |
Documentation:
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