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Volumn 3571 LNAI, Issue , 2005, Pages 932-943

Methods to determine the branching attribute in Bayesian multinets classifiers

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS; CONTEXT SENSITIVE GRAMMARS;

EID: 26944472782     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11518655_78     Document Type: Conference Paper
Times cited : (7)

References (28)
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    • (1996) Artificial Intelligence , vol.82 , pp. 45-74
    • Geiger, D.1    Heckerman, D.2
  • 7
    • 0036532762 scopus 로고    scopus 로고
    • Learning recursive bayesian multinets for data clustering by means of constructive induction
    • Peña, J.M., Lozano, J.A., Larrañaga, P.: Learning recursive bayesian multinets for data clustering by means of constructive induction. Machine Learning, 47 (2002) 63-89
    • (2002) Machine Learning , vol.47 , pp. 63-89
    • Peña, J.M.1    Lozano, J.A.2    Larrañaga, P.3
  • 9
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • Kohavi, R., John, G.H.: Wrappers for feature subset selection. Artificial Intelligence 97 (1997) 273-324
    • (1997) Artificial Intelligence , vol.97 , pp. 273-324
    • Kohavi, R.1    John, G.H.2
  • 10
    • 70350346892 scopus 로고
    • Use of distance measures, information measures and error bounds in feature evaluation
    • Krishnaiah, P.R., Kanal, L.N., eds., North-Holland Publishing Company, Amsterdan
    • Ben-Bassat, M.: Use of distance measures, information measures and error bounds in feature evaluation. In Krishnaiah, P.R., Kanal, L.N., eds.: Handbook of Statistics. Volume 2., North-Holland Publishing Company, Amsterdan (1982) 773-791
    • (1982) Handbook of Statistics , vol.2 , pp. 773-791
    • Ben-Bassat, M.1
  • 21
    • 34249832377 scopus 로고
    • A bayesian method for the induction of probabilistic networks from data
    • Cooper, G., Herskovits, E.: A bayesian method for the induction of probabilistic networks from data. Machine Learning 9 (1992) 309-347
    • (1992) Machine Learning , vol.9 , pp. 309-347
    • Cooper, G.1    Herskovits, E.2
  • 22
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz, G.: Estimating the dimension of a model. Annals of Statistics 6 (1978) 461-464
    • (1978) Annals of Statistics , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 23
    • 34249761849 scopus 로고
    • Learning bayesian networks: The combination of knowledge and statistical data
    • Heckerman, D., Geiger, D., Chickering, D.M.: Learning bayesian networks: The combination of knowledge and statistical data. Machine Learning 20 (1995) 197-243
    • (1995) Machine Learning , vol.20 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 26
    • 0002593344 scopus 로고
    • Multi-valued interval discretization of continuous-valued attributes for classification learning
    • Morgan Kaufmann, San Mateo
    • Fayyad, U., Irani, K.: Multi-valued interval discretization of continuous-valued attributes for classification learning. Proceeding of the 13th International joint Conference on Artificial Inteligence, Morgan Kaufmann, San Mateo, 1022-1027 (1993)
    • (1993) Proceeding of the 13th International Joint Conference on Artificial Inteligence , pp. 1022-1027
    • Fayyad, U.1    Irani, K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.