Association Classification Based on Compactness of Rules

@article{Niu2009AssociationCB,
  title={Association Classification Based on Compactness of Rules},
  author={Qiang Niu and Shixiong Xia and Lei Zhang},
  journal={2009 Second International Workshop on Knowledge Discovery and Data Mining},
  year={2009},
  pages={245-247}
}
Associative classification has high classification accuracy and strong flexibility. However, it still suffers from overfitting since the classification rules satisfied both minimum support and minimum confidence are returned as strong association rules back to the classifier. In this paper, we propose a new association classification method based on compactness of rules, it extends Apriori Algorithm¿which considers the interestingness, importance, overlapping relationships among rules. At last… CONTINUE READING

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