Classification Rule Learning with APRIORI-C

@inproceedings{Jovanoski2001ClassificationRL,
  title={Classification Rule Learning with APRIORI-C},
  author={Viktor Jovanoski and N. Lavrac},
  booktitle={EPIA},
  year={2001}
}
  • Viktor Jovanoski, N. Lavrac
  • Published in EPIA 2001
  • Computer Science
  • This paper presents the APRIORI-C algorithm, modifying the association rule learner APRIORI to learn classification rules. The algorithm achieves decreased time and space complexity, while still performing exhaustive search of the rule space. Other APRIORI-C improvements include feature subset selection and rule post-processing, leading to increased understandability of rules and increased accuracy in domains with unbalanced class distributions. In comparison with learners which use the… CONTINUE READING

    Tables and Topics from this paper.

    Subgroup Discovery with CN2-SD
    • 370
    • Open Access
    ROCCER: An Algorithm for Rule Learning Based on ROC Analysis
    • 45
    • Open Access
    ENDER: a statistical framework for boosting decision rules
    • 56
    • Open Access
    Solving Regression by Learning an Ensemble of Decision Rules
    • 29
    • Open Access
    Web usage mining for predicting final marks of students that use Moodle courses
    • 215
    • Highly Influenced
    • Open Access

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 24 REFERENCES
    Integrating Classification and Association Rule Mining
    • 2,463
    • Open Access
    Fast algorithms for mining association rules
    • 7,912
    • Open Access
    Mining the most interesting rules
    • 695
    • Open Access
    Estimating Attributes: Analysis and Extensions of RELIEF
    • 2,332
    • Open Access
    Constraint-based rule mining in large, dense databases
    • 333
    • Open Access
    Toward Optimal Feature Selection
    • 1,589
    • Open Access
    Partial Classification Using Association Rules
    • 258
    • Open Access