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Volumn , Issue , 2012, Pages

Enhancing classification performance of multi-class imbalanced data using the OAA-DB algorithm

Author keywords

artificial neural network; classification; complementary neural network; misclassification analysis; multi class imbalanced data; OAA; SMOTE

Indexed keywords

BALANCING TECHNIQUES; BINARY CLASSIFICATION; CLASSIFICATION ACCURACY; CLASSIFICATION PERFORMANCE; CLASSIFICATION TECHNIQUE; DATA CLASSIFICATION; IMBALANCED CLASS; IMBALANCED DATA; IMBALANCED DATA SETS; MACHINE LEARNING REPOSITORY; MISCLASSIFICATION ANALYSIS; MULTI-CLASS; MULTI-CLASS PROBLEMS; OAA; SMOTE; UNIVERSITY OF CALIFORNIA;

EID: 84865105427     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2012.6252450     Document Type: Conference Paper
Times cited : (18)

References (22)
  • 1
    • 78650556770 scopus 로고    scopus 로고
    • Survey on multi-class classification methods
    • November
    • M. Aly, "Survey on multi-class classification methods," Caltech, USA, Technical Report, November 2005.
    • (2005) Caltech, USA, Technical Report
    • Aly, M.1
  • 2
    • 33749240206 scopus 로고    scopus 로고
    • Multi-class pattern classification using neural networks
    • G. Ou and Y. L. Murphey, "Multi-class pattern classification using neural networks," Pattern Recognition, vol. 40, pp. 4-18, 2007.
    • (2007) Pattern Recognition , vol.40 , pp. 4-18
    • Ou, G.1    Murphey, Y.L.2
  • 4
    • 27144531570 scopus 로고    scopus 로고
    • A study of the behavior of several methods for balancing machine learning training data
    • G. E. A. P. A. Batista, R. C. Prati, and M. C. Monard, "A study of the behavior of several methods for balancing machine learning training data," SIGKDD Explorations Newsletter, vol. 6, pp. 20-29, 2004.
    • (2004) SIGKDD Explorations Newsletter , vol.6 , pp. 20-29
    • Batista, G.E.A.P.A.1    Prati, R.C.2    Monard, M.C.3
  • 9
    • 31344442851 scopus 로고    scopus 로고
    • Training cost-sensitive neural networks with methods addressing the class imbalance problem
    • Z.-H. Zhou and X.-Y. Liu, "Training cost-sensitive neural networks with methods addressing the class imbalance problem," IEEE Transactions on Knowledge and Data Engineering, vol. 18, pp. 63-77, 2006.
    • (2006) IEEE Transactions on Knowledge and Data Engineering , vol.18 , pp. 63-77
    • Zhou, Z.-H.1    Liu, X.-Y.2
  • 14
    • 77951220817 scopus 로고    scopus 로고
    • Binary classification using ensemble neural networks and interval neutrosophic sets
    • P. Kraipeerapun and C. C. Fung, "Binary classification using ensemble neural networks and interval neutrosophic sets," Neurocomput., vol. 72, pp. 2845-2856, 2009.
    • (2009) Neurocomput. , vol.72 , pp. 2845-2856
    • Kraipeerapun, P.1    Fung, C.C.2
  • 18
    • 78650207592 scopus 로고    scopus 로고
    • Classification of imbalanced data by combining the complementary neural network and SMOTE algorithm
    • Springer Berlin / Heidelberg
    • P. Jeatrakul, K. W. Wong, and C. C. Fung, "Classification of Imbalanced Data by Combining the Complementary Neural Network and SMOTE Algorithm," in Neural Information Processing. Models and Applications. vol. 6444: Springer Berlin / Heidelberg, 2010, pp. 152-159.
    • (2010) Neural Information Processing. Models and Applications , vol.6444 , pp. 152-159
    • Jeatrakul, P.1    Wong, K.W.2    Fung, C.C.3
  • 20
    • 36948999941 scopus 로고    scopus 로고
    • University of California, Irvine, School of Information and Computer Sciences
    • A. Asuncion and D. J. Newman, "UCI Machine Learning Repository," University of California, Irvine, School of Information and Computer Sciences, 2007.
    • (2007) UCI Machine Learning Repository
    • Asuncion, A.1    Newman, D.J.2
  • 22
    • 0034143132 scopus 로고    scopus 로고
    • Noise detection and elimination in data preprocessing: Experiments in medical domains
    • D. Gamberger, N. Lavrac, and S. Dzeroski, "Noise detection and elimination in data preprocessing: Experiments in medical domains," Applied Artificial Intelligence, vol. 14, pp. 205-223, 2000.
    • (2000) Applied Artificial Intelligence , vol.14 , pp. 205-223
    • Gamberger, D.1    Lavrac, N.2    Dzeroski, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.