A stochastic approach for association rule extraction

@article{Oliinyk2016ASA,
  title={A stochastic approach for association rule extraction},
  author={A. A. Oliinyk and Sergei A. Subbotin},
  journal={Pattern Recognition and Image Analysis},
  year={2016},
  volume={26},
  pages={419-426}
}
This paper addresses the problem of association rule extraction. To extract quantitative association rules from given sets of observations, a stochastic method is proposed. The developed method improves the reliability and interpretability of recognition models based on association rules, employs the stochastic approach to search through various combinations of sets of elements in association rules, and uses a priori information about the informativity of intervals of feature values. A system… CONTINUE READING

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References

Publications referenced by this paper.
Showing 1-10 of 17 references

The Way to Synthesize Diagnostic and Recognition Models on the Base of Hybrid

  • A. A. Oleinik, T. A. Zaiko, S. A. Subbotin
  • Neuro Fuzzy Technologies of Computa tional…
  • 2014
Highly Influential
13 Excerpts

Gen, Introduction to Evolutionary Algorithms (Decision Engineering

  • M. Yu
  • 2010
Highly Influential
8 Excerpts

Pattern Recognition and Image Preprocessing

  • S. Bow
  • 2002
Highly Influential
8 Excerpts

Discovery of Association Rules in Datasets via Evolutionary Algorithms (Lambert Acad

  • L. Petrala
  • Publ., Ham burg,
  • 2014

Inductive model of r  correct empirical forest

  • V. I. Donskoi, Yu. Yu. Dyulicheva
  • Proc . Int . Conf . on Inductive Simulation…
  • 2014

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