메뉴 건너뛰기




Volumn 214, Issue 2, 2008, Pages 381-392

An efficient modified boosting method for solving classification problems

Author keywords

Adaboost; Classification noise; Ensemble classifier; Kappa error diagram; Weak learner

Indexed keywords

ADA (PROGRAMMING LANGUAGE); ALGORITHMS; CLASSIFICATION (OF INFORMATION); ERROR ANALYSIS; PROBABILITY;

EID: 39049086240     PISSN: 03770427     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cam.2007.03.003     Document Type: Article
Times cited : (38)

References (27)
  • 1
    • 39049103754 scopus 로고    scopus 로고
    • C.L. Blake, C.J. Merz, UCI repository of machine learning databases, 1998, available from: 〈http://www.ics.uci.edu/∼mlearn/MLRepository.html〉.
    • C.L. Blake, C.J. Merz, UCI repository of machine learning databases, 1998, available from: 〈http://www.ics.uci.edu/∼mlearn/MLRepository.html〉.
  • 2
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. Bagging predictors. Mach. Learn. 24 (1996) 123-140
    • (1996) Mach. Learn. , vol.24 , pp. 123-140
    • Breiman, L.1
  • 3
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • Breiman L. Arcing classifiers. Ann. Statist. 26 (1998) 801-849
    • (1998) Ann. Statist. , vol.26 , pp. 801-849
    • Breiman, L.1
  • 5
    • 32544431928 scopus 로고    scopus 로고
    • Evolving hybrid ensembles of learning machines for better generalisation
    • Chandra A., and Yao X. Evolving hybrid ensembles of learning machines for better generalisation. Neurocomputing 69 (2006) 686-700
    • (2006) Neurocomputing , vol.69 , pp. 686-700
    • Chandra, A.1    Yao, X.2
  • 6
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting and randomization
    • Dietterich T. An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting and randomization. Mach. Learn. 40 (2000) 139-157
    • (2000) Mach. Learn. , vol.40 , pp. 139-157
    • Dietterich, T.1
  • 8
    • 58149321460 scopus 로고
    • Boosting a weak learning algorithm by majority
    • Freund Y. Boosting a weak learning algorithm by majority. Inform. and Comput. 121 (1995) 256-285
    • (1995) Inform. and Comput. , vol.121 , pp. 256-285
    • Freund, Y.1
  • 10
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Freund Y., and Schapire R. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. System Sci. 55 (1997) 119-139
    • (1997) J. Comput. System Sci. , vol.55 , pp. 119-139
    • Freund, Y.1    Schapire, R.2
  • 11
    • 0035470889 scopus 로고    scopus 로고
    • Greedy function approximation: a gradient boosting machine
    • Friedman J. Greedy function approximation: a gradient boosting machine. Ann. Statist. 29 (2001) 1189-1232
    • (2001) Ann. Statist. , vol.29 , pp. 1189-1232
    • Friedman, J.1
  • 12
  • 13
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: a statistical view of boosting
    • Friedman J., Hastie T., and Tibshirani R. Additive logistic regression: a statistical view of boosting. Ann. Statist. 28 (2000) 337-407
    • (2000) Ann. Statist. , vol.28 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 18
    • 35248862907 scopus 로고    scopus 로고
    • R. Meir, G. Rätsch, An introduction to boosting and leveraging, in: Lecturer Notes in Computer Science, vol. 2600, 2003, pp. 118-183.
    • R. Meir, G. Rätsch, An introduction to boosting and leveraging, in: Lecturer Notes in Computer Science, vol. 2600, 2003, pp. 118-183.
  • 19
    • 0000551189 scopus 로고    scopus 로고
    • Popular ensemble methods: an empirical study
    • Optiz D., and Maclin R. Popular ensemble methods: an empirical study. J. Artificial Intell. Res. 11 (1999) 169-198
    • (1999) J. Artificial Intell. Res. , vol.11 , pp. 169-198
    • Optiz, D.1    Maclin, R.2
  • 20
    • 85156192015 scopus 로고    scopus 로고
    • Generating accurate and diverse members of a neural-network ensemble
    • Opitz D.W., and Shavlik J.W. Generating accurate and diverse members of a neural-network ensemble. Neural Inform. Proc. Sys. 8 (1996) 535-541
    • (1996) Neural Inform. Proc. Sys. , vol.8 , pp. 535-541
    • Opitz, D.W.1    Shavlik, J.W.2
  • 23
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • Schapire R.E. The strength of weak learnability. Mach. Learn. 5 (1990) 197-227
    • (1990) Mach. Learn. , vol.5 , pp. 197-227
    • Schapire, R.E.1
  • 24
    • 0032280519 scopus 로고    scopus 로고
    • Boosting the margin: a new explanation for the effectiveness of voting methods
    • Schapire R.E., Freund Y., Bartlett P., and Lee W.S. Boosting the margin: a new explanation for the effectiveness of voting methods. Ann. Statist. 26 (1998) 1651-1686
    • (1998) Ann. Statist. , vol.26 , pp. 1651-1686
    • Schapire, R.E.1    Freund, Y.2    Bartlett, P.3    Lee, W.S.4
  • 25
    • 0242328690 scopus 로고
    • Embedding of linear programming in a simulated annealing algorithm for solving a mixed integer production planning problem
    • Teghem J., Pirlot M., and Antoniadis C. Embedding of linear programming in a simulated annealing algorithm for solving a mixed integer production planning problem. J. Comput. Appl. Math. 64 (1995) 92-101
    • (1995) J. Comput. Appl. Math. , vol.64 , pp. 92-101
    • Teghem, J.1    Pirlot, M.2    Antoniadis, C.3
  • 26
    • 85037997203 scopus 로고    scopus 로고
    • Committee machines
    • Hu Y.H., and Hwang J.-N. (Eds), CRC Press, Boca Raton
    • Tresp V. Committee machines. In: Hu Y.H., and Hwang J.-N. (Eds). Handbook for Neural Network Signal Processing (2001), CRC Press, Boca Raton
    • (2001) Handbook for Neural Network Signal Processing
    • Tresp, V.1
  • 27
    • 0034247206 scopus 로고    scopus 로고
    • Multiboosting: a technique for combining boosting and bagging
    • Webb G.I. Multiboosting: a technique for combining boosting and bagging. Mach. Learn. 40 (2000) 159-196
    • (2000) Mach. Learn. , vol.40 , pp. 159-196
    • Webb, G.I.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.