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Volumn 7461 LNCS, Issue , 2012, Pages 13-24

ABC-Miner: An ant-based Bayesian classification algorithm

Author keywords

[No Author keywords available]

Indexed keywords

ANT COLONY OPTIMIZATION (ACO); BAYESIAN CLASSIFICATION; BAYESIAN NETWORK CLASSIFIERS; BAYESIAN NETWORKS (BNS); DATA SETS; HEURISTIC SEARCH ALGORITHMS; HIGH QUALITY; LEARNING PROBLEM; METAHEURISTIC; NOVEL ALGORITHM; POSTERIOR PROBABILITY;

EID: 84866422636     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-32650-9_2     Document Type: Conference Paper
Times cited : (10)

References (21)
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    • Cooper, G.F.1    Herskovits, E.2
  • 7
    • 79959427276 scopus 로고    scopus 로고
    • Using ant colony optimization in learning Bayesian network equivalence classes
    • Daly, R., Shen, Q., Aitken, S.: Using ant colony optimization in learning Bayesian network equivalence classes. In: Proceedings of UKCI, pp. 111-118 (2006)
    • (2006) Proceedings of UKCI , pp. 111-118
    • Daly, R.1    Shen, Q.2    Aitken, S.3
  • 8
    • 68349117241 scopus 로고    scopus 로고
    • Learning Bayesian network equivalence classes with ant colony optimization
    • Daly, R., Shen, Q.: Learning Bayesian network equivalence classes with ant colony optimization. Journal of Artificial Intelligence Research, 391-447 (2009)
    • (2009) Journal of Artificial Intelligence Research , pp. 391-447
    • Daly, R.1    Shen, Q.2
  • 11
    • 0000220520 scopus 로고    scopus 로고
    • Learning Bayesian networks with local structure
    • Kluwer, Norwell
    • Friedman, N., Goldszmidt, M.: Learning Bayesian networks with local structure. Learning in Graphical Models, pp. 421-460. Kluwer, Norwell (1998)
    • (1998) Learning in Graphical Models , pp. 421-460
    • Friedman, N.1    Goldszmidt, M.2
  • 12
    • 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 Journal, 197-244 (1995)
    • (1995) Machine Learning Journal , pp. 197-244
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 14
    • 56449120614 scopus 로고    scopus 로고
    • CAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes
    • Dorigo, M., Birattari, M., Blum, C., Clerc, M., Stützle, T., Winfield, A.F.T. (eds.) ANTS 2008. Springer, Heidelberg
    • Otero, F.E.B., Freitas, A.A., Johnson, C.G.: cAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes. In: Dorigo, M., Birattari, M., Blum, C., Clerc, M., Stützle, T., Winfield, A.F.T. (eds.) ANTS 2008. LNCS, vol. 5217, pp. 48-59. Springer, Heidelberg (2008)
    • (2008) LNCS , vol.5217 , pp. 48-59
    • Otero, F.E.B.1    Freitas, A.A.2    Johnson, C.G.3
  • 15
    • 0036670786 scopus 로고    scopus 로고
    • Data mining with an ant colony optimization algorithm
    • Parpinelli, R.S., Lopes, H.S., Freitas, A.: Data mining with an ant colony optimization algorithm. In: IEEE TEC, pp. 321-332 (2002)
    • (2002) IEEE TEC , pp. 321-332
    • Parpinelli, R.S.1    Lopes, H.S.2    Freitas, A.3
  • 17
    • 69249179454 scopus 로고    scopus 로고
    • Using a Local Discovery Ant Algorithm for Bayesian Network Structure Learning
    • Pinto, P.C., Nägele, A., Dejori, M., Runkler, T.A., Costa, J.M.: Using a Local Discovery Ant Algorithm for Bayesian Network Structure Learning. In: IEEE TEC, pp. 767-779 (2009)
    • (2009) IEEE TEC , pp. 767-779
    • Pinto, P.C.1    Nägele, A.2    Dejori, M.3    Runkler, T.A.4    Costa, J.M.5
  • 18
    • 82355186008 scopus 로고    scopus 로고
    • Multiple pheromone types and other extensions to the Ant-Miner classification rule discovery algorithm
    • Salama, K.M., Abdelbar, A.M., Freitas, A.A.: Multiple pheromone types and other extensions to the Ant-Miner classification rule discovery algorithm. Swarm Intelligence Journal, 149-182 (2011)
    • (2011) Swarm Intelligence Journal , pp. 149-182
    • Salama, K.M.1    Abdelbar, A.M.2    Freitas, A.A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.