메뉴 건너뛰기




Volumn , Issue , 2007, Pages 320-331

On sample selection bias and its efficient correction via model averaging and unlabeled examples

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; MACHINE LEARNING; PROBABILITY DISTRIBUTIONS; SUPERVISED LEARNING;

EID: 70449134523     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972771.29     Document Type: Conference Paper
Times cited : (19)

References (13)
  • 1
    • 33845519968 scopus 로고    scopus 로고
    • Fan' et al 2005] Fan W., Davidson I., Zadrozny B. and Yu P., (2005), An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias, 5th IEEE International Conference on Data Mining, ICDM 2005.
    • Fan' et al 2005] Fan W., Davidson I., Zadrozny B. and Yu P., (2005), An Improved Categorization of Classifier's Sensitivity on Sample Selection Bias, 5th IEEE International Conference on Data Mining, ICDM 2005.
  • 2
    • 33749571093 scopus 로고    scopus 로고
    • Fan and Davidson, 2006] Fan W., and Davidson I., (2006) ReverseTesting: An Efficient Framework to Select Amongst Classifers under Sample Selection Bias, 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006.
    • Fan and Davidson, 2006] Fan W., and Davidson I., (2006) ReverseTesting: An Efficient Framework to Select Amongst Classifers under Sample Selection Bias, 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006.
  • 3
    • 70449095922 scopus 로고    scopus 로고
    • Davidson and Fan, 2006] Davidson I., and Fan W., (2006) When Efficient Model Averaging Out-Performs Boosting and Bagging, 17th European Conference on Machine Learning and 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD06).
    • Davidson and Fan, 2006] Davidson I., and Fan W., (2006) When Efficient Model Averaging Out-Performs Boosting and Bagging, 17th European Conference on Machine Learning and 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD06).
  • 4
    • 70449109197 scopus 로고    scopus 로고
    • Heckman, 1979] Heckman, J. (1979). Sample selection bias as a specification error. Econometrica, 47:153-161.
    • Heckman, 1979] Heckman, J. (1979). Sample selection bias as a specification error. Econometrica, 47:153-161.
  • 5
    • 85101444608 scopus 로고    scopus 로고
    • Little and Rubin, 2002] Little, R. and Rubin, D. (2002). Statistical Analysis with Missing Data. Wiley, 2nd edition.
    • Little and Rubin, 2002] Little, R. and Rubin, D. (2002). Statistical Analysis with Missing Data. Wiley, 2nd edition.
  • 6
    • 78149327484 scopus 로고    scopus 로고
    • Peng et. al 2003] Peng, K., Vucetic, S., Han, B., Xie H. and Obradovic, Z. (2003). Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining Proc. Third IEEE Int'l Conf. Data Mining, Melbourne, Fl, pp. 267-274.
    • Peng et. al 2003] Peng, K., Vucetic, S., Han, B., Xie H. and Obradovic, Z. (2003). Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining Proc. Third IEEE Int'l Conf. Data Mining, Melbourne, Fl, pp. 267-274.
  • 7
    • 27344454215 scopus 로고    scopus 로고
    • Chawla and Karakoulas, 2005] Chawla N. V. and Karakoulas G. (2005). Learning From Labeled And Unlabeled Data: An Empirical Study Across Techniques And Domains Journal of Artificial Intelligence and Research, 23, pages 331-366.
    • Chawla and Karakoulas, 2005] Chawla N. V. and Karakoulas G. (2005). Learning From Labeled And Unlabeled Data: An Empirical Study Across Techniques And Domains Journal of Artificial Intelligence and Research, Volume 23, pages 331-366.
  • 8
    • 70449088963 scopus 로고    scopus 로고
    • Huang et al., 2006] Huang, J., Smola, A., Gretton, A., Borgwardt, K., and Scholkopf, B. (2006). Correcting Sample Selection Bias by Unlabeled Data In Proceedings of Neural Information Processsing System Conference (NIPS'2006), December 4-6, 2006, Vancouver, BC, Canada.
    • Huang et al., 2006] Huang, J., Smola, A., Gretton, A., Borgwardt, K., and Scholkopf, B. (2006). Correcting Sample Selection Bias by Unlabeled Data In Proceedings of Neural Information Processsing System Conference (NIPS'2006), December 4-6, 2006, Vancouver, BC, Canada.
  • 9
    • 33749554765 scopus 로고    scopus 로고
    • Rosset et al., 2005] Rosset, S., Zhu, J., Zou, H., and Hastie, T. (2005). A method for inferring label sampling mechanisms in semisupervised learning. In Advances in Neural Information Processing Systems 17, pages 1161-1168. MIT Press.
    • Rosset et al., 2005] Rosset, S., Zhu, J., Zou, H., and Hastie, T. (2005). A method for inferring label sampling mechanisms in semisupervised learning. In Advances in Neural Information Processing Systems 17, pages 1161-1168. MIT Press.
  • 10
    • 12244265089 scopus 로고    scopus 로고
    • Smith and Elkan, 2004] Smith, A. and Elkan, C. (2004). A bayesian network framework for reject inference. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 286-295.
    • Smith and Elkan, 2004] Smith, A. and Elkan, C. (2004). A bayesian network framework for reject inference. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 286-295.
  • 12
    • 84945313388 scopus 로고    scopus 로고
    • Vittaut et al., 2002] Vittaut, J., Amini, M., and Gallinari, P. (2002), Learning Classification with Both Labeled and Unlabeled Data. In ECML 2002, pages 468-479.
    • Vittaut et al., 2002] Vittaut, J., Amini, M., and Gallinari, P. (2002), Learning Classification with Both Labeled and Unlabeled Data. In ECML 2002, pages 468-479.
  • 13
    • 14344263218 scopus 로고    scopus 로고
    • Zadrozny, 2004] Zadrozny, B. (2004). Learning and evaluating classifiers under sample selection bias. In Proceedings of the 21th International Conference on Machine Learning.
    • Zadrozny, 2004] Zadrozny, B. (2004). Learning and evaluating classifiers under sample selection bias. In Proceedings of the 21th International Conference on Machine Learning.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.