A survey of interestingness measures for knowledge discovery

@article{McGarry2005ASO,
  title={A survey of interestingness measures for knowledge discovery},
  author={Kenneth McGarry},
  journal={Knowledge Eng. Review},
  year={2005},
  volume={20},
  pages={39-61}
}
It is a well-known fact that the data mining process can generate many hundreds and often thousands of patterns from data. [...] Key Method These so-called interestingness measures are generally divided into two categories: objective measures based on the statistical strengths or properties of the discovered patterns and subjective measures that are derived from the user's beliefs or expectations of their particular problem domain. We evaluate the strengths and weaknesses of the various interestingness measures…Expand Abstract

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