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Volumn 23, Issue , 2012, Pages 315-331

Learning from Imbalanced Data: Evaluation Matters

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EID: 84885636932     PISSN: 18684394     EISSN: 18684408     Source Type: Book Series    
DOI: 10.1007/978-3-642-23166-7_12     Document Type: Article
Times cited : (63)

References (31)
  • 1
    • 22944452794 scopus 로고    scopus 로고
    • Applying support vector machines to imbalanced datasets
    • In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.), Springer, Heidelberg
    • Akbani, R., Kwek, S.S., Japkowicz, N.: Applying support vector machines to imbalanced datasets. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) ECML 2004. LNCS (LNAI), vol. 3201, pp. 39-50. Springer, Heidelberg (2004)
    • (2004) ECML 2004. LNCS (LNAI , vol.3201 , pp. 39-50
    • Akbani, R.1    Kwek, S.S.2    Japkowicz, N.3
  • 2
    • 27144531570 scopus 로고    scopus 로고
    • A study of the behavior of several methods for balancing machine learning training data
    • Batista, G.E.A.P.A., Prati, R.C., Monard, M.C.: A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explorations 6(1) (2004)
    • (2004) SIGKDD Explorations , vol.6 , Issue.1
    • Batista, G.E.A.P.A.1    Prati, R.C.2    Monard, M.C.3
  • 6
    • 0346586663 scopus 로고    scopus 로고
    • SMOTE: Synthetic Minority Oversampling TEchnique
    • Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: Synthetic Minority Oversampling TEchnique. JAIR 16, 321-357 (2002)
    • (2002) JAIR , vol.16 , pp. 321-357
    • Chawla, N.V.1    Bowyer, K.W.2    Hall, L.O.3    Kegelmeyer, W.P.4
  • 7
    • 84885603502 scopus 로고    scopus 로고
    • Automatically Countering Imbalance and Its Empirical Relationship to Cost
    • Chawla, N.V., Cieslak, D., Hall, L.O., Joshi, A.: Automatically Countering Imbalance and Its Empirical Relationship to Cost. In: DMKD (2009)
    • (2009) DMKD
    • Chawla, N.V.1    Cieslak, D.2    Hall, L.O.3    Joshi, A.4
  • 8
    • 84886450557 scopus 로고    scopus 로고
    • Learning decision trees on unbalanced data
    • Cieslak, D.A., Chawla, N.V.: Learning decision trees on unbalanced data. In: ECML (2008)
    • (2008) ECML
    • Cieslak, D.A.1    Chawla, N.V.2
  • 10
    • 29644438050 scopus 로고    scopus 로고
    • Statistical Comparisons of Classifiers over Multiple Data Sets
    • Demsar, J.: Statistical Comparisons of Classifiers over Multiple Data Sets. JMLR 7, 1-30 (2006)
    • (2006) JMLR , vol.7 , pp. 1-30
    • Demsar, J.1
  • 11
    • 84885615343 scopus 로고    scopus 로고
    • Direct Marketing Association
    • Direct Marketing Association. The dmef data set library, http://www.directworks.org/Educators/Default.aspx?id=632
    • The Dmef Data Set Library
  • 12
    • 0002419948 scopus 로고    scopus 로고
    • Beyond independence: Conditions for the optimality of the simple bayesian classifier
    • Domingos, P., Pazzani, M.J.: Beyond independence: Conditions for the optimality of the simple bayesian classifier. In: ICML (1996)
    • (1996) ICML
    • Domingos, P.1    Pazzani, M.J.2
  • 13
    • 0012130233 scopus 로고    scopus 로고
    • Learning Goal Oriented Bayesian Networks for Risk Management
    • Ezawa, K.J., Singh, M., Norton, S.W.: Learning Goal Oriented Bayesian Networks for Risk Management. In: ICML, pp. 139-147 (1996)
    • (1996) ICML , pp. 139-147
    • Ezawa, K.J.1    Singh, M.2    Norton, S.W.3
  • 14
    • 84885623494 scopus 로고    scopus 로고
    • A method for discovering the insignificance of one's best classifier and the unlearnability of a classification task
    • Forman, G.: A method for discovering the insignificance of one's best classifier and the unlearnability of a classification task. In: Data Mining Lessons Learned Workshop, ICML (2002)
    • (2002) Data Mining Lessons Learned Workshop, ICML
    • Forman, G.1
  • 15
    • 33646433421 scopus 로고    scopus 로고
    • Beware the null hypothesis: Critical value tables for evaluating classifiers
    • In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.), Springer, Heidelberg
    • Forman, G., Cohen, I.: Beware the null hypothesis: Critical value tables for evaluating classifiers. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), vol. 3720, pp. 133-145. Springer, Heidelberg (2005)
    • (2005) ECML 2005. LNCS (LNAI , vol.3720 , pp. 133-145
    • Forman, G.1    Cohen, I.2
  • 16
    • 69549133517 scopus 로고    scopus 로고
    • Measuring classifier performance: A coherent alternative to the area under the ROC curve
    • Hand, D.J.: Measuring classifier performance: a coherent alternative to the area under the ROC curve. Machine Learning 77(1), 103-123 (2009)
    • (2009) Machine Learning , vol.77 , Issue.1 , pp. 103-123
    • Hand, D.J.1
  • 17
    • 34547995826 scopus 로고    scopus 로고
    • Experimental perspectives on learning from imbalanced data
    • In: Ghahramani, Z. (ed.), ACM, New York
    • Hulse, J.V., Khoshgoftaar, T.M., Napolitano, A.: Experimental perspectives on learning from imbalanced data. In: Ghahramani, Z. (ed.) ICML, pp. 935-942. ACM, New York (2007)
    • (2007) ICML , pp. 935-942
    • Hulse, J.V.1    Khoshgoftaar, T.M.2    Napolitano, A.3
  • 18
    • 0031998121 scopus 로고    scopus 로고
    • Machine Learning for the Detection of Oil Spills in Satellite Radar Images
    • Kubat, M., Holte, R., Matwin, S.: Machine Learning for the Detection of Oil Spills in Satellite Radar Images. Machine Learning 30, 195-215 (1998)
    • (1998) Machine Learning , vol.30 , pp. 195-215
    • Kubat, M.1    Holte, R.2    Matwin, S.3
  • 21
    • 33947284406 scopus 로고    scopus 로고
    • Boosted classification trees and class probability/ quantile estimation
    • Mease, D., Wyner, A.J., Buja, A.: Boosted classification trees and class probability/ quantile estimation. Journal of Machine Learning Research 8(3), 557-562 (2007)
    • (2007) Journal of Machine Learning Research , vol.8 , Issue.3 , pp. 557-562
    • Mease, D.1    Wyner, A.J.2    Buja, A.3
  • 25
    • 4744344959 scopus 로고    scopus 로고
    • Classification and Knowledge Discovery in Protein Databases
    • Radivojac, P., Chawla, N.V., Dunker, K., Obradovic, Z.: Classification and Knowledge Discovery in Protein Databases. JBI 37(4), 224-239 (2004)
    • (2004) JBI , vol.37 , Issue.4 , pp. 224-239
    • Radivojac, P.1    Chawla, N.V.2    Dunker, K.3    Obradovic, Z.4
  • 26
    • 62349122663 scopus 로고    scopus 로고
    • Countering imbalanced datasets to improve adverse drug event predictive models in labor and delivery
    • Tafts, L.M., et al.: Countering imbalanced datasets to improve adverse drug event predictive models in labor and delivery. JBI (2009)
    • (2009) JBI
    • Tafts, L.M.1
  • 28
    • 20844441675 scopus 로고    scopus 로고
    • Kba: Kernel boundary alignment considering imbalanced data distribution
    • Wu, G., Chang, E.Y.: Kba: Kernel boundary alignment considering imbalanced data distribution. IEEE TKDE 17(6), 786-795 (2005)
    • (2005) IEEE TKDE , vol.17 , Issue.6 , pp. 786-795
    • Wu, G.1    Chang, E.Y.2
  • 29
    • 36849083008 scopus 로고    scopus 로고
    • Local Decomposition for Rare Class Analysis
    • Wu, J., Xiong, H., Wu, P., Chen, J.: Local Decomposition for Rare Class Analysis. In: Proceedings of KDD, pp. 814-823 (2007)
    • (2007) Proceedings of KDD , pp. 814-823
    • Wu, J.1    Xiong, H.2    Wu, P.3    Chen, J.4
  • 30
    • 0035789316 scopus 로고    scopus 로고
    • Learning and making decisions when costs and probabilities are both unknown
    • Zadrozny, B., Elkan, C.: Learning and making decisions when costs and probabilities are both unknown. In: Proceedings KDD (2001)
    • (2001) Proceedings KDD
    • Zadrozny, B.1    Elkan, C.2
  • 31
    • 31344442851 scopus 로고    scopus 로고
    • Training cost-sensitive neural networks with methods addressing the class imbalance problem
    • Zhou, Z., Liu, X.: Training cost-sensitive neural networks with methods addressing the class imbalance problem. IEEE TKDE 18(1), 63-77 (2006)
    • (2006) IEEE TKDE , vol.18 , Issue.1 , pp. 63-77
    • Zhou, Z.1    Liu, X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.