CURLER: finding and visualizing nonlinear correlation clusters

@inproceedings{Tung2005CURLERFA,
  title={CURLER: finding and visualizing nonlinear correlation clusters},
  author={Anthony K. H. Tung and Xin Xu and B. C. Ooi},
  booktitle={SIGMOD '05},
  year={2005}
}
  • Anthony K. H. Tung, Xin Xu, B. C. Ooi
  • Published in SIGMOD '05 2005
  • Computer Science
  • While much work has been done in finding linear correlation among subsets of features in high-dimensional data, work on detecting nonlinear correlation has been left largely untouched. [...] Key Method To avoid this problem, we propose a novel concept called co-sharing level which captures both spatial proximity and cluster orientation when judging similarity between clusters.Expand Abstract
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