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Volumn 4701 LNAI, Issue , 2007, Pages 490-501

Finding the right family: Parent and child selection for averaged one-dependence estimators

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; ERROR CORRECTION; PARAMETER ESTIMATION; PROBABILITY;

EID: 38049141398     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74958-5_45     Document Type: Conference Paper
Times cited : (11)

References (27)
  • 1
    • 0022848955 scopus 로고
    • Feature selection and extraction
    • Young, T.Y, Fu, K.-S, eds, Academic Press, New York
    • Kittler, J.: Feature selection and extraction. In: Young, T.Y., Fu, K.-S. (eds.) Handbook of Pattern Recognition and Image Processing, pp. 60-81. Academic Press, New York (1986)
    • (1986) Handbook of Pattern Recognition and Image Processing , pp. 60-81
    • Kittler, J.1
  • 2
    • 85031799549 scopus 로고
    • Semi-naive Bayesian classifier
    • Session on Machine learning, pp, Springer, Berlin
    • Kononenko, I.: Semi-naive Bayesian classifier. In: Proc. 6th European Working Session on Machine learning, pp. 206-219. Springer, Berlin (1991)
    • (1991) Proc. 6th European Working , pp. 206-219
    • Kononenko, I.1
  • 3
    • 84886741606 scopus 로고
    • Induction of recursive Bayesian classifiers
    • Springer, Berlin
    • Langley, P.: Induction of recursive Bayesian classifiers. In: Proc. 1993 European Conf. Machine Learning, pp. 153-164. Springer, Berlin (1993)
    • (1993) Proc. 1993 European Conf. Machine Learning , pp. 153-164
    • Langley, P.1
  • 5
    • 85156137079 scopus 로고    scopus 로고
    • Scaling up the accuracy of naive-Bayes classifiers: A decision-tree hybrid
    • ACM Press, New York
    • Kohavi, R.: Scaling up the accuracy of naive-Bayes classifiers: a decision-tree hybrid. In: Proc. 2nd ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining, pp. 202 207. ACM Press, New York (1996)
    • (1996) Proc. 2nd ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining , pp. 202-207
    • Kohavi, R.1
  • 7
    • 85010067887 scopus 로고    scopus 로고
    • Learning limited dependence Bayesian classifiers
    • AAAI Press, Menlo Park, CA
    • Sahami, M.: Learning limited dependence Bayesian classifiers. In: Proc. 2nd Int. Conf. Knowledge Discovery in Databases, pp. 334-338. AAAI Press, Menlo Park, CA (1996)
    • (1996) Proc. 2nd Int. Conf. Knowledge Discovery in Databases , pp. 334-338
    • Sahami, M.1
  • 8
    • 0007152230 scopus 로고    scopus 로고
    • Efficient learning of selective Bayesian network classifiers
    • Morgan Kaufmann, San Francisco
    • Singh, M., Provan, G.M.: Efficient learning of selective Bayesian network classifiers. In: Proc. 13th Int. Conf. Machine Learning, pp. 453-461. Morgan Kaufmann, San Francisco (1996)
    • (1996) Proc. 13th Int. Conf. Machine Learning , pp. 453-461
    • Singh, M.1    Provan, G.M.2
  • 11
    • 0002610991 scopus 로고    scopus 로고
    • Learning augmented Bayesian classifers: A comparison of distribution-based and classification-based approaches
    • Keogh, E.J., Pazzani, M.J.: Learning augmented Bayesian classifers: A comparison of distribution-based and classification-based approaches. In: Proc. Int. Workshop on Artificial Intelligence and Statistics, pp. 225-230 (1999)
    • (1999) Proc. Int. Workshop on Artificial Intelligence and Statistics , pp. 225-230
    • Keogh, E.J.1    Pazzani, M.J.2
  • 12
    • 0034301677 scopus 로고    scopus 로고
    • Lazy learning of Bayesian rules
    • Zheng, Z., Webb, G.I.: Lazy learning of Bayesian rules. Machine Learning 41(1), 53-84 (2000)
    • (2000) Machine Learning , vol.41 , Issue.1 , pp. 53-84
    • Zheng, Z.1    Webb, G.I.2
  • 13
    • 14844351034 scopus 로고    scopus 로고
    • Not so naive Bayes: Aggregating one-dependence estimators
    • Webb, G.I., Boughton, J., Wang, Z.: Not so naive Bayes: Aggregating one-dependence estimators. Machine Learning 58(1), 5-24 (2005)
    • (2005) Machine Learning , vol.58 , Issue.1 , pp. 5-24
    • Webb, G.I.1    Boughton, J.2    Wang, Z.3
  • 14
    • 38049113544 scopus 로고    scopus 로고
    • Cerquides, J., Mantaras, R.L.D.: Robust Bayesian linear classifier ensembles. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), 3720, pp. 70-81. Springer, Heidelberg (2005)
    • Cerquides, J., Mantaras, R.L.D.: Robust Bayesian linear classifier ensembles. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), vol. 3720, pp. 70-81. Springer, Heidelberg (2005)
  • 15
    • 33749265151 scopus 로고    scopus 로고
    • Efficient lazy elimination for averaged-one dependence estimators
    • ACM Press, New York
    • Zheng, F., Webb, G.I.: Efficient lazy elimination for averaged-one dependence estimators. In: Proc. 23th Int. Conf. Machine Learning (ICML 2006), pp. 1113-1120. ACM Press, New York (2006)
    • (2006) Proc. 23th Int. Conf. Machine Learning (ICML , pp. 1113-1120
    • Zheng, F.1    Webb, G.I.2
  • 16
    • 33745444617 scopus 로고    scopus 로고
    • Classification using hierarchical naive Bayes models
    • Langseth, H., Nielsen, T.D.: Classification using hierarchical naive Bayes models. Machine Learning 63(2), 135-159 (2006)
    • (2006) Machine Learning , vol.63 , Issue.2 , pp. 135-159
    • Langseth, H.1    Nielsen, T.D.2
  • 21
    • 0002419948 scopus 로고    scopus 로고
    • Beyond independence: Conditions for the optimality of the simple Bayesian classifier
    • Morgan Kaufmann, San Francisco
    • Domingos, P., Pazzani, M.J.: Beyond independence: Conditions for the optimality of the simple Bayesian classifier. In: Proc. 13th Int. Conf. Machine Learning, pp. 105-112. Morgan Kaufmann, San Francisco (1996)
    • (1996) Proc. 13th Int. Conf. Machine Learning , pp. 105-112
    • Domingos, P.1    Pazzani, M.J.2
  • 22
    • 85099325734 scopus 로고
    • Irrelevant features and the subset selection problem
    • Morgan Kaufmann, San Francisco, CA
    • John, G.H., Kohavi, R., Pfleger, K.: Irrelevant features and the subset selection problem. In: Proc. 11th Int. Conf. Machine Learning, pp. 121-129. Morgan Kaufmann, San Francisco, CA (1994)
    • (1994) Proc. 11th Int. Conf. Machine Learning , pp. 121-129
    • John, G.H.1    Kohavi, R.2    Pfleger, K.3
  • 24
    • 0002593344 scopus 로고
    • Multi-interval discretization of continuous-valued attributes for classification learning
    • Morgan Kaufmann, San Francisco
    • Fayyad, U.M., Irani, K.B.: Multi-interval discretization of continuous-valued attributes for classification learning. In: Proc. 13th Int. Joint Conf. Artificial Intelligence (IJCAI-93), pp. 1022-1029. Morgan Kaufmann, San Francisco (1993)
    • (1993) Proc. 13th Int. Joint Conf. Artificial Intelligence (IJCAI-93) , pp. 1022-1029
    • Fayyad, U.M.1    Irani, K.B.2
  • 25
    • 0003006556 scopus 로고
    • Estimating probabilities: A crucial task in machine learning
    • Pitman, London
    • Cestnik, B.: Estimating probabilities: A crucial task in machine learning. In: Proc. 9th European Conf. Artificial Intelligence, pp. 147-149. Pitman, London (1990)
    • (1990) Proc. 9th European Conf. Artificial Intelligence , pp. 147-149
    • Cestnik, B.1
  • 27
    • 0034247206 scopus 로고    scopus 로고
    • Multiboosting: A technique for combining boosting and wagging
    • Webb, G.I.: Multiboosting: A technique for combining boosting and wagging. Machine Learning 40(2), 159-196 (2000)
    • (2000) Machine Learning , vol.40 , Issue.2 , pp. 159-196
    • Webb, G.I.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.