메뉴 건너뛰기




Volumn 5032 LNAI, Issue , 2008, Pages 13-24

Assessing the impact of changing environments on classifier performance

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; ROBUST CONTROL;

EID: 44649189946     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-68825-9_2     Document Type: Conference Paper
Times cited : (43)

References (13)
  • 2
    • 33748991193 scopus 로고    scopus 로고
    • Cost curves: An improved method for visualizing classifier performance
    • Drummond, C., Holte, R.C.: Cost curves: An improved method for visualizing classifier performance. Machine Learning 65(1), 95-130 (2006)
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 95-130
    • Drummond, C.1    Holte, R.C.2
  • 3
    • 33745886270 scopus 로고    scopus 로고
    • Classifier technology and the illusion of progress
    • Hand, D.J.: Classifier technology and the illusion of progress. Statistical Sciences 21(1), 1-15 (2006)
    • (2006) Statistical Sciences , vol.21 , Issue.1 , pp. 1-15
    • Hand, D.J.1
  • 4
    • 33745903917 scopus 로고    scopus 로고
    • Elaboration on two points raised in classifier technology and the illusion of progress
    • Holte, R.: Elaboration on two points raised in classifier technology and the illusion of progress. Statistical Science 21(1) (2006)
    • (2006) Statistical Science , vol.21 , Issue.1
    • Holte, R.1
  • 6
    • 33845990606 scopus 로고    scopus 로고
    • Why question machine learning evaluation methods? an illustrative review of the shortcomings of current methods
    • Boston, USA
    • Japkowicz, N.: Why question machine learning evaluation methods? an illustrative review of the shortcomings of current methods. In: AAAI-2006 Workshop on Evaluation Methods for Machine Learning, Boston, USA (2006)
    • (2006) AAAI-2006 Workshop on Evaluation Methods for Machine Learning
    • Japkowicz, N.1
  • 8
    • 85166317163 scopus 로고    scopus 로고
    • Approaches to online learning and concept drift for user identification in computer security
    • Lane, T., Brodley, C.E.: Approaches to online learning and concept drift for user identification in computer security. In: Knowledge Discovery and Data Mining, pp. 259-263 (1998)
    • (1998) Knowledge Discovery and Data Mining , pp. 259-263
    • Lane, T.1    Brodley, C.E.2
  • 9
    • 0035283313 scopus 로고    scopus 로고
    • Robust classification systems for imprecise environments
    • Provost, F., Fawcett, T.: Robust classification systems for imprecise environments. Machine Learning 42(3), 203-231 (2001)
    • (2001) Machine Learning , vol.42 , Issue.3 , pp. 203-231
    • Provost, F.1    Fawcett, T.2
  • 10
    • 0036134369 scopus 로고    scopus 로고
    • Adjusting a classifier for new a priori probabilities: A simple procedure
    • Saerens, M., Latinne, P., Decaestecker, C.: Adjusting a classifier for new a priori probabilities: A simple procedure. Neural Computation 14, 21-41 (2002)
    • (2002) Neural Computation , vol.14 , pp. 21-41
    • Saerens, M.1    Latinne, P.2    Decaestecker, C.3
  • 13
    • 34547980509 scopus 로고    scopus 로고
    • Yamazaki, K., Kawanabe, M., Watanabe, S., Sugiyama, M., Müller, K.: Asymptotic bayesian generalization error when training and test distributions are different. In: ICML 2007, pp. 1079-1086. ACM Press, New York (2007)
    • Yamazaki, K., Kawanabe, M., Watanabe, S., Sugiyama, M., Müller, K.: Asymptotic bayesian generalization error when training and test distributions are different. In: ICML 2007, pp. 1079-1086. ACM Press, New York (2007)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.