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Volumn 19, Issue 6, 2006, Pages 438-444

Using multiple and negative target rules to make classifiers more understandable

Author keywords

Association rules; Classification; Negative and multiple rules

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER SCIENCE; KNOWLEDGE BASED SYSTEMS; MATHEMATICAL MODELS;

EID: 33747878571     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2006.03.003     Document Type: Article
Times cited : (9)

References (22)
  • 1
    • 33747884147 scopus 로고    scopus 로고
    • R. Agrawal, R. Srikant. Fast algorithms for mining association rules in large databases. In: Proceedings of the 20th International Conference on Very Large Databases, Santiago, Chile, 1994, pp. 487-499.
  • 2
    • 34247340013 scopus 로고    scopus 로고
    • M. Antonie, O.R. Zaiane. Mining positive and negative association rules: an approach for confined rules. In: European Conference on Principles and Practice of Knowledge Discovery in Databases, 2004, pp. 27-38.
  • 3
    • 0031698969 scopus 로고    scopus 로고
    • A.Savasere, E.Omiecinski, S.B. Navathe. Mining for strong negative associations in a large database of customer transactions. In: Proceedings of International Conference on Data Engineering ICDE98, 1998, pp 494-502.
  • 5
    • 23044517681 scopus 로고    scopus 로고
    • Constraint-based rule mining in large, dense database
    • Bayardo R., Agrawal R., and Gunopulos D. Constraint-based rule mining in large, dense database. Data Min. Knowl. Disc. J. 4 2/3 (2000) 217-240
    • (2000) Data Min. Knowl. Disc. J. , vol.4 , Issue.2-3 , pp. 217-240
    • Bayardo, R.1    Agrawal, R.2    Gunopulos, D.3
  • 6
    • 33747884877 scopus 로고    scopus 로고
    • E.K.C. Blake and C.J. Merz. UCI repository of machine learning databases, http://www.ics.uci.edu/≫mlearn/MLRepository.html, 1998.
  • 7
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. Bagging predictors. Mach. Learn. 24 (1996) 123-140
    • (1996) Mach. Learn. , vol.24 , pp. 123-140
    • Breiman, L.1
  • 8
    • 85015191605 scopus 로고    scopus 로고
    • P. Clark, R. Boswell. Rule induction with CN2: Some recent improvements. In: Machine Learning-EWSL-91, 1991, pp. 151-163.
  • 9
    • 34249966007 scopus 로고
    • The CN2 induction algorithm
    • Clark P., and Niblett T. The CN2 induction algorithm. Mach. Learn. 3 4 (1989) 261-283
    • (1989) Mach. Learn. , vol.3 , Issue.4 , pp. 261-283
    • Clark, P.1    Niblett, T.2
  • 10
    • 33747892761 scopus 로고    scopus 로고
    • Y. Freund, R.E. Schapire. Experiments with a new boosting algorithm. In: International Conference on Machine Learning, 1996, pp. 148-156.
  • 11
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Freund Y., and Schapire R.E. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comp. Syst. Sci. 5 1 (1997) 119-139
    • (1997) J. Comp. Syst. Sci. , vol.5 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 12
    • 2442449952 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation: a frequent-pattern tree approach
    • Han J., Pei J., Yin Y., and Mao R. Mining frequent patterns without candidate generation: a frequent-pattern tree approach. Data Min. Knowl. Disc. J. (2004) 53-87
    • (2004) Data Min. Knowl. Disc. J. , pp. 53-87
    • Han, J.1    Pei, J.2    Yin, Y.3    Mao, R.4
  • 13
    • 84942772223 scopus 로고    scopus 로고
    • F. Hussain, H. Liu, E. Suzuki, H. Lu. Exception rule mining with a relative interestingness measure. In: Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD 00), LNCS, 2000, pp 86-97.
  • 14
    • 0036722344 scopus 로고    scopus 로고
    • Mining the optimal class association rule set
    • Li J., Shen H., and Topor R. Mining the optimal class association rule set. Knowl-Based Syst. 15 7 (2002) 399-405
    • (2002) Knowl-Based Syst. , vol.15 , Issue.7 , pp. 399-405
    • Li, J.1    Shen, H.2    Topor, R.3
  • 16
    • 33747878927 scopus 로고    scopus 로고
    • B. Liu, W. Hsu, Y. Ma. Integrating classification and association rule mining. In: Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998, pp. 27-31.
  • 17
    • 84974710130 scopus 로고    scopus 로고
    • B. Liu, Y. Ma, C. Wong. Improving an association rule based classifier. In: Fourth European Conference on Principles and Practice of Knowledge Discovery in Databases PKDD, 2000, pp. 504-509.
  • 18
    • 33747875662 scopus 로고    scopus 로고
    • R. Michalski, I. Mozetic, J. Hong, N. Lavrac. The AQ15 inductive learning system: an overview and experiments. In: Proceedings of IMAL 1986, Orsay, 1986. University de Paris-Sud.
  • 20
    • 3843055627 scopus 로고    scopus 로고
    • Efficient mining of both positive and negative association rules
    • Wu X., Zhang C., and Zhang S. Efficient mining of both positive and negative association rules. ACM T. Inform. Syst. 22 3 (2004) 381-405
    • (2004) ACM T. Inform. Syst. , vol.22 , Issue.3 , pp. 381-405
    • Wu, X.1    Zhang, C.2    Zhang, S.3
  • 21
    • 33747884262 scopus 로고    scopus 로고
    • X. Yin, J. Han. CPAR: Classification based on predictive association rules. In: Proceedings of 2003 SIAM International Conference on Data Mining (SDM'03), 2003.
  • 22
    • 84883861471 scopus 로고    scopus 로고
    • X. Yuan, B.P. Buckles, Z. Yuan, J. Zhang. Mining negative association rules. In: Proceedings of the Seventh IEEE Symposium on Computers and Communications, 2002, pp. 623-628.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.