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Volumn 2, Issue , 2006, Pages 861-866

An approach to spam detection by Naive bayes ensemble based on decision induction

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; DECISION THEORY; DECISION TREES; EMBEDDED SYSTEMS; MAXIMUM LIKELIHOOD;

EID: 34547499822     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2006.253725     Document Type: Conference Paper
Times cited : (43)

References (18)
  • 1
    • 0031246271 scopus 로고    scopus 로고
    • Decision Tree Induction Based on Efficient Tree Restructuring
    • E. U. Paul, C. B. Neil, and A. C. Jeffery, "Decision Tree Induction Based on Efficient Tree Restructuring," Machine Learning, Vol. 29, 1997, pp. 5-44
    • (1997) Machine Learning , vol.29 , pp. 5-44
    • Paul, E.U.1    Neil, C.B.2    Jeffery, A.C.3
  • 3
    • 34247360512 scopus 로고    scopus 로고
    • Spam Filtering Using Character-Level Markov Models: Experiments for the TREC 2005 Spam Track
    • A. Bratko, B. Filipic, "Spam Filtering Using Character-Level Markov Models: Experiments for the TREC 2005 Spam Track," Proc. of the Fourteenth Text REtrieval Conference, 2005
    • (2005) Proc. of the Fourteenth Text REtrieval Conference
    • Bratko, A.1    Filipic, B.2
  • 9
    • 0031269184 scopus 로고    scopus 로고
    • On the Optimality of the Simple Bayesian Classifier Under Zero-One Loss
    • P. Domingos, M. Pazzani, "On the Optimality of the Simple Bayesian Classifier Under Zero-One Loss", Machine Learning, 1997, pp. 103-130
    • (1997) Machine Learning , pp. 103-130
    • Domingos, P.1    Pazzani, M.2
  • 10
    • 0030211964 scopus 로고    scopus 로고
    • Bagging Predictors
    • L. Breiman, "Bagging Predictors", Machine Learning, 1996, pp. 123-140
    • (1996) Machine Learning , pp. 123-140
    • Breiman, L.1
  • 13
    • 27744552792 scopus 로고    scopus 로고
    • Efficient Information Theoretic Strategies for Classifier Combination, Feature Extraction and Performance Evaluation in Improving False Positives and False Negatives for Spam E-mail Filtering
    • V. Zorkadis, D.A. Karras, M. Panayotou, "Efficient Information Theoretic Strategies for Classifier Combination, Feature Extraction and Performance Evaluation in Improving False Positives and False Negatives for Spam E-mail Filtering", Neural Networks, Vol. 18, 2005, pp. 799-807
    • (2005) Neural Networks , vol.18 , pp. 799-807
    • Zorkadis, V.1    Karras, D.A.2    Panayotou, M.3
  • 15
    • 0032594950 scopus 로고    scopus 로고
    • Support Vector Machines for Spam Categorization
    • H. Drucker, D. H.Wu, V. N. Vapnik, "Support Vector Machines for Spam Categorization", IEEE Trans. on Neural Networks, vol. 10, no. 5, 1999, pp. 1048-1054
    • (1999) IEEE Trans. on Neural Networks , vol.10 , Issue.5 , pp. 1048-1054
    • Drucker, H.1    Wu, D.H.2    Vapnik, V.N.3
  • 16
    • 24344458137 scopus 로고    scopus 로고
    • Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min- Redundancy
    • H. Peng, F. Long, C. Ding, "Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min- Redundancy", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 27, no. 8, 2005, pp. 1226-1237
    • (2005) IEEE Trans. on Pattern Analysis and Machine Intelligence , vol.27 , Issue.8 , pp. 1226-1237
    • Peng, H.1    Long, F.2    Ding, C.3
  • 17
    • 0041965980 scopus 로고    scopus 로고
    • Cluster Ensembles - A Knowledge Reuse Framework for Combining Multiple Partitions
    • A. Strehl, J. Ghosh, "Cluster Ensembles - A Knowledge Reuse Framework for Combining Multiple Partitions", Journal on Machine Learning Research (JMLR), 2002, pp.583-617
    • (2002) Journal on Machine Learning Research (JMLR) , pp. 583-617
    • Strehl, A.1    Ghosh, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.