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Volumn 25, Issue 6, 2002, Pages 645-650

Incremental Bayes classification model

Author keywords

Conjugate Dirichlet distribution; Data mining; Incremental learning; Simple Bayes

Indexed keywords

DATA MINING; LEARNING ALGORITHMS; PARAMETER ESTIMATION;

EID: 0036625155     PISSN: 02544164     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (21)

References (8)
  • 2
    • 0031276011 scopus 로고    scopus 로고
    • Bayesian network classifier
    • Nir Friedman, Dan Geiger. Bayesian network classifier. Machine Learning, 1997, 29: 131-163
    • (1997) Machine Learning , vol.29 , pp. 131-163
    • Friedman, N.1    Geiger, D.2
  • 3
    • 0031269184 scopus 로고    scopus 로고
    • On the optimality of the simple Bayesian classifier under zero-loss
    • Dominigos, P, Pazzani M. On the optimality of the simple Bayesian classifier under zero-loss. Machine Learning, 1997, 29: 103-130
    • (1997) Machine Learning , vol.29 , pp. 103-130
    • Dominigos, P.1    Pazzani, M.2
  • 4
    • 38249020853 scopus 로고
    • Incremental evaluation and construction of defeasible probabilistic models
    • D'Ambrosio B. Incremental evaluation and construction of defeasible probabilistic models. International Journal of Approximate Reasoning, 1990, 4: 233-260
    • (1990) International Journal of Approximate Reasoning , vol.4 , pp. 233-260
    • D'Ambrosio, B.1
  • 5
    • 0002559343 scopus 로고    scopus 로고
    • Hierarchical Bayes for test classification
    • Melbourne, Australia
    • Shivakumar Vaithyanathan, Jianchang Mao, Byron Dom. Hierarchical bayes for test classification. In: Proc PRICAI'2000, Melbourne, Australia, 2000. 36-43
    • (2000) Proc. PRICAI'2000 , pp. 36-43
    • Vaithyanathan, S.1    Mao, J.2    Dom, B.3
  • 7
    • 0031630992 scopus 로고    scopus 로고
    • Learning to classify the text from labeled and unlabeled documents
    • Madison, Wisconsin
    • Kamal Nigam et al. Learning to classify the text from labeled and unlabeled documents. In: Proc 15th National Conference on Artificial Intelligence. Madison, Wisconsin, 1998. 792-799
    • (1998) Proc. 15th National Conference on Artificial Intelligence , pp. 792-799
    • Nigam, K.1
  • 8
    • 0011481369 scopus 로고    scopus 로고
    • Semi-supervised web mining based Bayesian latent semantic analysis
    • accepted, Chinese source
    • Gong Xiu-Jun, Shi Zhong-Zhi. Semi-supervised web mining based Bayesian latent semantic analysis. Journal of Software, 2002, accepted (in Chinese)
    • (2002) Journal of Software
    • Gong, X.-J.1    Shi, Z.-Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.