A toolbox for K

@article{Leisch2006ATF,
  title={A toolbox for K},
  author={F. Leisch},
  journal={Comput. Stat. Data Anal.},
  year={2006},
  volume={51},
  pages={526-544}
}
  • F. Leisch
  • Published 2006
  • Mathematics, Computer Science
  • Comput. Stat. Data Anal.
A methodological and computational framework for centroid-based partitioning cluster analysis using arbitrary distance or similarity measures is presented. The power of high-level statistical computing environments like R enables data analysts to easily try out various distance measures with only minimal programming effort. A new variant of centroid neighborhood graphs is introduced which gives insight into the relationships between adjacent clusters. Artificial examples and a case study from… Expand
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