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Mining negative rules using GRD

Mining negative rules using GRD. D. R. Thiruvady and G. I. Webb PAKDD 2004. Outline. Introduction OPUS GRD Conclusion. Introduction. Association rule A ==> B (A is antecedent ,B is consequent) Negative Rules Either antecedent or consequent or both are negated.

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Mining negative rules using GRD

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  1. Mining negative rules using GRD D. R. Thiruvady and G. I. Webb PAKDD 2004

  2. Outline • Introduction • OPUS • GRD • Conclusion

  3. Introduction • Association rule • A ==> B (A is antecedent ,B is consequent) • Negative Rules • Either antecedent or consequent or both are negated

  4. Optimized Pruning for Unordered Search (OPUS)

  5. Generate Rule Discovery (GRD) • Extends OPUS by remove the requirement that consequent be single variable • K number of rules replace minimum support

  6. GRD • Four measures with respect to a rule XY

  7. GRD • Symbol

  8. Properties

  9. Properties

  10. Properties

  11. Properties

  12. GRD • Symbol • CurrentLHS：Init ψ • AvailableLHS：Init Antecedent • AvailableRHS：Init Consequent • Function • Insolution(ac)：rule ac in solution • Proven(X)：pruning rules provided to the algorithm prove the proposition X

  13. GRD algorithm Prune 1 Prune 2 Prune 3,4,5

  14. GRD algorithm2 Prune 6

  15. Pruning

  16. Pruning

  17. Pruning

  18. Update Constraints

  19. Negative with GRD

  20. Conclusion • Disadvantage • Search space too large

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