메뉴 건너뛰기




Volumn 13, Issue 6, 2009, Pages 861-872

On the window size for classification in changing environments

Author keywords

Concept drift; Moving window size; Streaming data; Training sample size

Indexed keywords


EID: 77649158823     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/IDA-2009-0397     Document Type: Article
Times cited : (64)

References (19)
  • 6
    • 33749618778 scopus 로고    scopus 로고
    • Learning with drift detection
    • Advances in Artificial Intelligence, SBIA 2004, 17th Brazilian Symposium on Artificial Intelligence, of, Springer Verlag
    • J. Gama, P. Medas, G. Castillo and P. Rodrigues, Learning with drift detection. In Advances in Artificial Intelligence - SBIA 2004, 17th Brazilian Symposium on Artificial Intelligence, volume 3171 of Lecture Notes in Computer Science, pages 286-295. Springer Verlag, 2004.
    • (2004) Lecture Notes in Computer Science , vol.3171 , pp. 286-295
    • Gama, J.1    Medas, P.2    Castillo, G.3    Rodrigues, P.4
  • 11
    • 77649160407 scopus 로고    scopus 로고
    • Incremental learning and concept drift: Editor's introduction
    • M. Kubat, J. Gama and P. Utgoff, Incremental learning and concept drift: Editor's introduction, Intelligent Data Analysis 8(3) (2004), 211-212.
    • (2004) Intelligent Data Analysis , vol.8 , Issue.3 , pp. 211-212
    • Kubat, M.1    Gama, J.2    Utgoff, P.3
  • 13
    • 1542748813 scopus 로고    scopus 로고
    • Using selective memory to track concept drift effectively
    • Salzburg, Austria, ACTA Press
    • M.M. Lazarescu and S. Venkatesh, Using selective memory to track concept drift effectively. In Intelligent Systems and Control, volume 388, Salzburg, Austria, 2003. ACTA Press.
    • (2003) Intelligent Systems and Control , vol.388
    • Lazarescu, M.M.1    Venkatesh, S.2
  • 14
    • 0026120032 scopus 로고
    • Small sample size effects in statistical pattern recognition: Recommendations for practitioners
    • S.J. Raudys and A.K. Jain, Small sample size effects in statistical pattern recognition: Recommendations for practitioners, IEEE Transactions on Pattern Analysis and Machine Intelligence 13(3) (1991), 252-264.
    • (1991) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.13 , Issue.3 , pp. 252-264
    • Raudys, S.J.1    Jain, A.K.2
  • 15
    • 0019020917 scopus 로고
    • On dimensionality, sample size, classification error and complexity of classification algorithm in pattern recognition
    • S.J. Raudys and V. Pikelis, On dimensionality, sample size, classification error and complexity of classification algorithm in pattern recognition, IEEE Transactions on Pattern Analysis Machine Intelligence 2 (1980), 242-252.
    • (1980) IEEE Transactions on Pattern Analysis Machine Intelligence , vol.2 , pp. 242-252
    • Raudys, S.J.1    Pikelis, V.2
  • 17
    • 0030126609 scopus 로고    scopus 로고
    • Learning in the presence of concept drift and hidden contexts
    • G. Widmer and M. Kubat, Learning in the presence of concept drift and hidden contexts, Machine Learning 23 (1996), 69-101.
    • (1996) Machine Learning , vol.23 , pp. 69-101
    • Widmer, G.1    Kubat, M.2
  • 18
    • 0012902924 scopus 로고    scopus 로고
    • Special Issue on Context Sensitivity and Concept Drift
    • G. Widmer and M. Kubat, Special Issue on Context Sensitivity and Concept Drift, Machine Learning 32, 1998.
    • (1998) Machine Learning , vol.32
    • Widmer, G.1    Kubat, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.