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Volumn , Issue , 2008, Pages 322-329

Probabilistic and Graphical Model based Genetic Algorithm Driven Clustering with Instance-level Constraints

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; CLUSTER ANALYSIS; EVOLUTIONARY ALGORITHMS; FEATURE EXTRACTION; FLOW OF SOLIDS; GENETIC ALGORITHMS; GRAPH THEORY; GRAPHIC METHODS; KNOWLEDGE BASED SYSTEMS; PROBABILISTIC LOGICS; PROBABILITY;

EID: 55749113361     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2008.4630817     Document Type: Conference Paper
Times cited : (9)

References (19)
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    • D. Klein, S. S. Kamvar and C. Manning, From Instance-level Constraints to Space-level Constraints: Making the most of the prior knowledge in data clustering, Proc. Nineteenth Int'l Conf. Machine Learning, pp. 307-314, 2002.
    • (2002) Proc. Nineteenth Int'l Conf. Machine Learning , pp. 307-314
    • Klein, D.1    Kamvar, S.S.2    Manning, C.3
  • 9
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    • A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
    • M. Laszlo and S. Mukherjee, A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering, IEEE Tran. Pattern Analysis and Machine Intelligence, vol. 28, pp. 533-543, 2006.
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    • Laszlo, M.1    Mukherjee, S.2
  • 11
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    • Removing the Genetics from the Standard Genetic Algorithm
    • S. Baluja and S. Davis, Removing the Genetics from the Standard Genetic Algorithm, Proc. Int'l Conf. Machine Learning, pp. 38-46, 1995.
    • (1995) Proc. Int'l Conf. Machine Learning , pp. 38-46
    • Baluja, S.1    Davis, S.2
  • 12
    • 78049265488 scopus 로고    scopus 로고
    • J. De Bonet, C. Isbell, and P. Viola, MIMIC: Finding Optima by Estimating Probability Densities, Proc. Advances in Neural Information Processing Systems, pp. 424-431, 1997.
    • J. De Bonet, C. Isbell, and P. Viola, MIMIC: Finding Optima by Estimating Probability Densities, Proc. Advances in Neural Information Processing Systems, pp. 424-431, 1997.
  • 13
    • 0001955592 scopus 로고    scopus 로고
    • Using Optimal Dependency-Trees for Combinatorial Optimization: Learning the Structure of the Search Space
    • S. Baluja and S. Davies, Using Optimal Dependency-Trees for Combinatorial Optimization: Learning the Structure of the Search Space, Proc. the Fourteenth Int'l Conf. on Machine Learning, pp. 30-38, 1997.
    • (1997) Proc. the Fourteenth Int'l Conf. on Machine Learning , pp. 30-38
    • Baluja, S.1    Davies, S.2
  • 16
    • 17744402661 scopus 로고    scopus 로고
    • Feature Subset Selection by Bayesian Network based Optimization
    • I. Inza, P. Larranaga and R. Etxeberria etc., Feature Subset Selection by Bayesian Network based Optimization. Artificial Intelligence, Vol. 123, pp. 157-184, 2000.
    • (2000) Artificial Intelligence , vol.123 , pp. 157-184
    • Inza, I.1    Larranaga, P.2    Etxeberria etc, R.3
  • 17
    • 0036778916 scopus 로고    scopus 로고
    • for Generating Additive Clustering Models with Limited Complexity
    • L. Michael, A Simple Method for Generating Additive Clustering Models with Limited Complexity, Journal of Machine Learning, Vol. 49, pp39-58, 2002.
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    • Michael, L.1    Simple Method, A.2
  • 18
    • 2442661659 scopus 로고    scopus 로고
    • Q. Zhang and H. Muhleubein, On the Convergence of A Class of Estimation of Distribution Algorithms, IEEE Tran. Evolutionary Computation, 8(2), pp. 127-136, 2004.
    • Q. Zhang and H. Muhleubein, On the Convergence of A Class of Estimation of Distribution Algorithms, IEEE Tran. Evolutionary Computation, Vol. 8(2), pp. 127-136, 2004.
  • 19
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    • N. Shental, A. Bar-Hillel T. Hertz and D. Weinshall, Computing Gaussian Mixture Models with EM using equivalence constraints, Advances in Neural Information Processing Systems 8(2), 2003.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.