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Volumn , Issue , 2010, Pages 1945-1946

Learning from Concept Drifting Data Streams with Unlabeled Data

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; DATA MINING; SUPERVISED LEARNING;

EID: 80052596334     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (10)
  • 1
    • 77958553145 scopus 로고    scopus 로고
    • Exploiting unlabeled data in concept drift learning
    • D. H. Widyantoro. 2007. Exploiting unlabeled data in concept drift learning. Jurnal Informatika 8(1): 54-62.
    • (2007) Jurnal Informatika , vol.8 , Issue.1 , pp. 54-62
    • Widyantoro, D. H.1
  • 2
    • 0035789299 scopus 로고    scopus 로고
    • Mining Time-changing Data Streams
    • G. Hulten, L. Spencer, and P. Domingos. 2001. Mining Time-changing Data Streams. In KDD'01, 97-106.
    • (2001) KDD'01 , pp. 97-106
    • Hulten, G.1    Spencer, L.2    Domingos, P.3
  • 3
    • 70350664414 scopus 로고    scopus 로고
    • Issues in Evaluation of Stream Learning Algorithms
    • J. Gama, R. Sebastião, and P. P. Rodrigues. 2009. Issues in Evaluation of Stream Learning Algorithms. In KDD'09, 329-338.
    • (2009) KDD'09 , pp. 329-338
    • Gama, J.1    Sebastião, R.2    Rodrigues, P. P.3
  • 4
    • 34547992192 scopus 로고    scopus 로고
    • Kddcup99 data set. 1999. http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html
    • (1999) Kddcup99 data set
  • 6
    • 67049160126 scopus 로고    scopus 로고
    • A Practical Approach to Classify Evolving Data Streams: Training with Limited Amount of Labeled Data
    • M. M. Masud, J. Gao, K. Latifur, and J. W. Han. 2008. A Practical Approach to Classify Evolving Data Streams: Training with Limited Amount of Labeled Data. In ICDM'08 929-934.
    • (2008) ICDM'08 , pp. 929-934
    • Masud, M. M.1    Gao, J.2    Latifur, K.3    Han, J. W.4
  • 7
    • 70350214945 scopus 로고    scopus 로고
    • Concept Drifting Detection on Noisy Streaming Data in Random Ensemble Decision Trees
    • P. P. Li, X. G. Hu, Q. H. Liang, and Y. J. Gao. 2009. Concept Drifting Detection on Noisy Streaming Data in Random Ensemble Decision Trees. In MLDM'09, 236-250.
    • (2009) MLDM'09 , pp. 236-250
    • Li, P. P.1    Hu, X. G.2    Liang, Q. H.3    Gao, Y. J.4
  • 8
    • 77958550972 scopus 로고    scopus 로고
    • Detecting Changes in Unlabeled Data Streams Using Martingale
    • S. S. Ho, and H. Wechsler. 2007. Detecting Changes in Unlabeled Data Streams Using Martingale. In IJCAI'07, 1912-1917.
    • (2007) IJCAI'07 , pp. 1912-1917
    • Ho, S. S.1    Wechsler, H.2
  • 9
    • 78449279203 scopus 로고    scopus 로고
    • Clustering-training for Data Stream Mining
    • S. Wu, C. Yang, and J. Zhou. 2006. Clustering-training for Data Stream Mining. In ICDMW'06, 653-656.
    • (2006) ICDMW'06 , pp. 653-656
    • Wu, S.1    Yang, C.2    Zhou, J.3
  • 10
    • 85167422495 scopus 로고    scopus 로고
    • Yahoo Shopping Web Services. http://developer.yahoo.com.everything.html


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.