Evolutionary multi objective optimization for rule mining: a review

@article{Srinivasan2011EvolutionaryMO,
  title={Evolutionary multi objective optimization for rule mining: a review},
  author={Sujatha Srinivasan and Sivakumar Ramakrishnan},
  journal={Artificial Intelligence Review},
  year={2011},
  volume={36},
  pages={205-248}
}
Evolutionary multi objective optimization (EMOO) systems are evolutionary systems which are used for optimizing various measures of the evolving system. Rule mining has gained attention in the knowledge discovery literature. The problem of discovering rules with specific properties is treated as a multi objective optimization problem. The objectives to be optimized being the metrics like accuracy, comprehensibility, surprisingness, novelty to name a few. There are a variety of EMOO algorithms… CONTINUE READING

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  • 2016
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References

Publications referenced by this paper.
SHOWING 1-10 OF 34 REFERENCES

Introduction to Agent Mining Interaction and Integration

  • Data Mining and Multi-agent Integration
  • 2009
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules

  • 2008 Eighth International Conference on Hybrid Intelligent Systems
  • 2008
VIEW 12 EXCERPTS
HIGHLY INFLUENTIAL

Multiobjective Classification Rule Mining

  • Multiobjective Problem Solving from Nature
  • 2008
VIEW 11 EXCERPTS
HIGHLY INFLUENTIAL

Toward evolving consistent, complete, and compact fuzzy rule sets for classification problems

  • 2008 3rd International Workshop on Genetic and Evolving Systems
  • 2008
VIEW 21 EXCERPTS
HIGHLY INFLUENTIAL

A multi-objective genetic programming approach to developing Pareto optimal decision trees

H Zhao
  • Decis Supp Syst
  • 2007
VIEW 15 EXCERPTS
HIGHLY INFLUENTIAL

A review of evolutionary algorithms for data minin, soft computing for knowledge discovery and data mining

AA Freitas
  • 2007
VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

Evolutionary Multiobjective Design of Fuzzy Rule-Based Systems

  • 2007 IEEE Symposium on Foundations of Computational Intelligence
  • 2007
VIEW 15 EXCERPTS
HIGHLY INFLUENTIAL