메뉴 건너뛰기




Volumn 26, Issue 1, 2013, Pages 98-129

Exploiting unlabeled data to enhance ensemble diversity

Author keywords

Diversity; Ensemble learning; Machine learning; Unlabeled data

Indexed keywords

BASE LEARNERS; DATA SETS; DIVERSITY; ENSEMBLE LEARNING; ENSEMBLE METHODS; ERROR PRONES; GENERALIZATION ABILITY; LABELED DATA; SEMI-SUPERVISED; TRAINING DATA; UNLABELED DATA;

EID: 84872409305     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-011-0243-9     Document Type: Article
Times cited : (66)

References (48)
  • 3
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • 1425957 0858.68080
    • Breiman L (1996) Bagging predictors. Mach Learn 24(2): 123-140
    • (1996) Mach Learn , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 6
    • 72149122081 scopus 로고    scopus 로고
    • Regularized negative correlation learning for neural network ensemble
    • 10.1109/TNN.2009.2034144
    • Chen HH, Yao X (2009) Regularized negative correlation learning for neural network ensemble. IEEE Trans Neural Netw 20(12): 1962-1979
    • (2009) IEEE Trans Neural Netw , vol.20 , Issue.12 , pp. 1962-1979
    • Chen, H.H.1    Yao, X.2
  • 7
    • 85162060750 scopus 로고    scopus 로고
    • Regularized boost for semi-supervised learning
    • J.C. Platt D. Koller Y. Singer S. Roweis (eds) MIT Press Cambridge, MA
    • Chen K, Wang S (2008) Regularized boost for semi-supervised learning. In: Platt JC, Koller D, Singer Y, Roweis S (eds) Advances in neural information processing systems, vol 20. MIT Press, Cambridge, MA, pp 281-288
    • (2008) Advances in Neural Information Processing Systems, Vol 20 , pp. 281-288
    • Chen, K.1    Wang, S.2
  • 8
    • 78649326338 scopus 로고    scopus 로고
    • Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions
    • 10.1109/TPAMI.2010.92
    • Chen K, Wang S (2011) Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions. IEEE Trans Pattern Anal Mach Intell 33(1): 129-143
    • (2011) IEEE Trans Pattern Anal Mach Intell , vol.33 , Issue.1 , pp. 129-143
    • Chen, K.1    Wang, S.2
  • 11
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • 2274360 1222.68184
    • Demšar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7: 1-30
    • (2006) J Mach Learn Res , vol.7 , pp. 1-30
    • Demšar, J.1
  • 15
    • 84983110889 scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • M.B. Vitányi (eds) Springer Berlin
    • Freund Y, Schapire RE (1995) A decision-theoretic generalization of on-line learning and an application to boosting. In: Vitányi PMB (ed) Lecture notes in computer science, vol 904. Springer, Berlin, pp 23-37
    • (1995) Lecture Notes in Computer Science, Vol 904 , pp. 23-37
    • Freund, Y.1    Schapire, R.E.2
  • 16
    • 0035420134 scopus 로고    scopus 로고
    • Design of effective neural network ensembles for image classification processes
    • 10.1016/S0262-8856(01)00045-2
    • Giacinto G, Roli F (2001) Design of effective neural network ensembles for image classification processes. Image Vis Comput 19(9/10): 699-707
    • (2001) Image Vis Comput , vol.19 , Issue.910 , pp. 699-707
    • Giacinto, G.1    Roli, F.2
  • 18
    • 85054435084 scopus 로고
    • Neural network ensembles, cross validation, and active learning
    • G. Tesauro D.S. Touretzky T.K. Leen (eds) MIT Press Cambridge, MA
    • Krogh A, Vedelsby J (1995) Neural network ensembles, cross validation, and active learning. In: Tesauro G, Touretzky DS, Leen TK (eds) Advances in neural information processing systems, vol 7. MIT Press, Cambridge, MA, pp 231-238
    • (1995) Advances in Neural Information Processing Systems, Vol 7 , pp. 231-238
    • Krogh, A.1    Vedelsby, J.2
  • 19
    • 0037403516 scopus 로고    scopus 로고
    • Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
    • 1027.68113 10.1023/A:1022859003006
    • Kuncheva LI, Whitaker CJ (2003) Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy. Mach Learn 51(2): 181-207
    • (2003) Mach Learn , vol.51 , Issue.2 , pp. 181-207
    • Kuncheva, L.I.1    Whitaker, C.J.2
  • 21
    • 36249007597 scopus 로고    scopus 로고
    • Improve computer-aided diagnosis with machine learning techniques using undiagnosed samples
    • 10.1109/TSMCA.2007.904745
    • Li M, Zhou ZH (2007) Improve computer-aided diagnosis with machine learning techniques using undiagnosed samples. IEEE Trans Syst Man Cybern A Syst Hum 37(6): 1088-1098
    • (2007) IEEE Trans Syst Man Cybern A Syst Hum , vol.37 , Issue.6 , pp. 1088-1098
    • Li, M.1    Zhou, Z.H.2
  • 22
    • 0033485370 scopus 로고    scopus 로고
    • Ensemble learning via negative correlation
    • 10.1016/S0893-6080(99)00073-8
    • Liu Y, Yao X (1999a) Ensemble learning via negative correlation. Neural Netw 12(10): 1399-1404
    • (1999) Neural Netw , vol.12 , Issue.10 , pp. 1399-1404
    • Liu, Y.1    Yao, X.2
  • 23
    • 0033280266 scopus 로고    scopus 로고
    • Simultaneous training of negatively correlated neural networks in an ensemble
    • 10.1109/3477.809027
    • Liu Y, Yao X (1999b) Simultaneous training of negatively correlated neural networks in an ensemble. IEEE Trans Syst Man Cybern B Cybern 29(6): 716-725
    • (1999) IEEE Trans Syst Man Cybern B Cybern , vol.29 , Issue.6 , pp. 716-725
    • Liu, Y.1    Yao, X.2
  • 26
    • 0002550596 scopus 로고    scopus 로고
    • Functional gradient techniques for combining hypotheses
    • A. Smola Bartlett B. Schölkopf D. Schuurmans (eds) MIT Press Cambridge
    • Mason L, Bartlett P, Baxter J, Frean M (2000) Functional gradient techniques for combining hypotheses. In: Smola A, Bartlett P, Schölkopf B, Schuurmans D (eds) Advances in large margin classifiers. MIT Press, Cambridge, pp 221-246
    • (2000) Advances in Large Margin Classifiers , pp. 221-246
    • Mason, L.1    Bartlett, P.2    Baxter, J.3    Frean, M.4
  • 31
    • 0030356238 scopus 로고    scopus 로고
    • Actively searching for an effective neural network ensemble
    • 10.1080/095400996116802
    • Opitz DW, Shavlik JW (1996) Actively searching for an effective neural network ensemble. Connection Science 8(3-4): 337-353
    • (1996) Connection Science , vol.8 , Issue.3-4 , pp. 337-353
    • Opitz, D.W.1    Shavlik, J.W.2
  • 32
    • 0031244715 scopus 로고    scopus 로고
    • Software diversity: Practical statistics for its measurement and exploitation
    • 10.1016/S0950-5849(97)00023-2
    • Partridge D, Krzanowski WJ (1997) Software diversity: practical statistics for its measurement and exploitation. Inf Softw Technol 39(10): 707-717
    • (1997) Inf Softw Technol , vol.39 , Issue.10 , pp. 707-717
    • Partridge, D.1    Krzanowski, W.J.2
  • 33
    • 0030367578 scopus 로고    scopus 로고
    • Ensemble learning using decorrelated neural networks
    • 10.1080/095400996116820
    • Rosen BE (1996) Ensemble learning using decorrelated neural networks. Connect Sci 8(3): 373-383
    • (1996) Connect Sci , vol.8 , Issue.3 , pp. 373-383
    • Rosen, B.E.1
  • 38
    • 0001884644 scopus 로고
    • Individual comparisons by ranking methods
    • 10.2307/3001968
    • Wilcoxon F (1945) Individual comparisons by ranking methods. Biometrics 1: 80-83
    • (1945) Biometrics , vol.1 , pp. 80-83
    • Wilcoxon, F.1
  • 39
    • 0026692226 scopus 로고
    • Stacked generalization
    • 2849783 10.1016/S0893-6080(05)80023-1
    • Wolpert DH (1992) Stacked generalization. Neural Netw 5(2): 241-259
    • (1992) Neural Netw , vol.5 , Issue.2 , pp. 241-259
    • Wolpert, D.H.1
  • 42
    • 70350346030 scopus 로고    scopus 로고
    • Ensemble learning
    • S.Z. Li (eds) Springer Berlin
    • Zhou ZH (2009a) Ensemble learning. In: Li SZ (ed) Encyclopedia of biometrics. Springer, Berlin
    • (2009) Encyclopedia of Biometrics
    • Zhou, Z.H.1
  • 44
    • 3042634798 scopus 로고    scopus 로고
    • NeC4.5: Neural ensemble based C4.5
    • 2119228 10.1109/TKDE.2004.11
    • Zhou ZH, Jiang Y (2004) NeC4.5: neural ensemble based C4.5. IEEE Trans Knowl Data Eng 16(6): 770-773
    • (2004) IEEE Trans Knowl Data Eng , vol.16 , Issue.6 , pp. 770-773
    • Zhou, Z.H.1    Jiang, Y.2
  • 45
    • 28244448186 scopus 로고    scopus 로고
    • Tri-training: Exploiting unlabeled data using three classifiers
    • 10.1109/TKDE.2005.186
    • Zhou ZH, Li M (2005) Tri-training: exploiting unlabeled data using three classifiers. IEEE Trans Knowl Data Eng 17(11): 1529-1541
    • (2005) IEEE Trans Knowl Data Eng , vol.17 , Issue.11 , pp. 1529-1541
    • Zhou, Z.H.1    Li, M.2
  • 46
    • 77956708689 scopus 로고    scopus 로고
    • Semi-supervised learning by disagreement
    • 10.1007/s10115-009-0209-z
    • Zhou ZH, Li M (2010) Semi-supervised learning by disagreement. Knowl Inf Syst 24(3): 415-439
    • (2010) Knowl Inf Syst , vol.24 , Issue.3 , pp. 415-439
    • Zhou, Z.H.1    Li, M.2
  • 48
    • 33745456231 scopus 로고    scopus 로고
    • Technical report 1530, Department of Computer Science, University of Wisconsin at Madison, Madison, WI
    • Zhu X (2006) Semi-supervised learning literature survey. Technical report 1530, Department of Computer Science, University of Wisconsin at Madison, Madison, WI
    • (2006) Semi-supervised Learning Literature Survey
    • Zhu, X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.