Improved cluster partition in principal component analysis guided clustering
Principal component analysis (PCA) guided clustering approach is widely used in high dimensional data to improve the efficiency of K- means cluster solutions. Typically, Pearson correlation is used in PCA to provide an eigen-analysis to obtain the associated components that account for most of the v...
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| 主要な著者: | , , |
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| フォーマット: | 論文 |
| 出版事項: |
2013
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/id/eprint/40261/ http://dx.doi.org/10.5120/13156-0839 |
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