메뉴 건너뛰기




Volumn 2, Issue 3, 2002, Pages 203-217

Learning from data: A tutorial with emphasis on modern pattern recognition methods

Author keywords

Boosting; Data analysis; Electronic nose; Ensemble methods; Learning; Pattern recognition

Indexed keywords

BOUNDARY CONDITIONS; DATA ACQUISITION; DATA REDUCTION; LEARNING SYSTEMS; PROBLEM SOLVING; STATISTICAL METHODS; THEOREM PROVING;

EID: 0346649878     PISSN: 1530437X     EISSN: None     Source Type: Journal    
DOI: 10.1109/JSEN.2002.800686     Document Type: Article
Times cited : (45)

References (54)
  • 3
    • 2542461872 scopus 로고    scopus 로고
    • A general framework for learning from data and an application to three electronic nose datasets
    • Brighton, U.K., July
    • M. Pardo, E. Dalcanale, and G. Sberveglieri, "A general framework for learning from data and an application to three electronic nose datasets," in 7th Int. Symp. Olfaction Electron. Nose, Brighton, U.K., July 2000.
    • (2000) 7th Int. Symp. Olfaction Electron. Nose
    • Pardo, M.1    Dalcanale, E.2    Sberveglieri, G.3
  • 7
    • 0001626006 scopus 로고
    • An initial examination of the data (with discussion)
    • C. Chatfield, "An initial examination of the data (with discussion)," J. Roy. Statist. Soc. A, vol. 148, pp. 214-253, 1985.
    • (1985) J. Roy. Statist. Soc. A , vol.148 , pp. 214-253
    • Chatfield, C.1
  • 12
    • 0001044176 scopus 로고
    • Neural networks and their applications
    • C. Bishop, "Neural networks and their applications," Rev. Sci. Instrum., vol. 65, no. 6, pp. 1803-1832, 1994.
    • (1994) Rev. Sci. Instrum. , vol.65 , Issue.6 , pp. 1803-1832
    • Bishop, C.1
  • 13
    • 26444485236 scopus 로고    scopus 로고
    • Neural networks: A pattern recognition perspective
    • E. Fiesler and R. Beale, Eds. New York: Oxford Univ. Press, [Online]
    • _, "Neural networks: A pattern recognition perspective," in Handbook of Neural Computation, E. Fiesler and R. Beale, Eds. New York: Oxford Univ. Press, 1996. [Online]. Available: http://www.ncrg.aston.ac.uk/.
    • (1996) Handbook of Neural Computation
  • 16
    • 0003271452 scopus 로고
    • Stopped training and other remedies for overfilling
    • [Online]
    • W. S. Sarle, "Stopped training and other remedies for overfilling," in Proc. 27th Symp. on Interface Comput. Sci. Statist., 1995, [Online]. Available: ftp://ftp.sas.com/pub/neural/inter95.ps.Z, pp. 352-360.
    • (1995) Proc. 27th Symp. on Interface Comput. Sci. Statist. , pp. 352-360
    • Sarle, W.S.1
  • 17
    • 0001025418 scopus 로고
    • Bayesian interpolation
    • D. J. C. MacKay, "Bayesian interpolation," Neural Comput., vol. 4, pp. 415-447, 1992.
    • (1992) Neural Comput. , vol.4 , pp. 415-447
    • MacKay, D.J.C.1
  • 26
    • 0032280519 scopus 로고    scopus 로고
    • A new explanation for the effectiveness of voting methods
    • R. E. Schapire, Y. Freund, P. Bartlett, and W. Lee, "A new explanation for the effectiveness of voting methods," Ann. Statist., vol. 26, no. 3, pp. 1651-1686, 1998.
    • (1998) Ann. Statist. , vol.26 , Issue.3 , pp. 1651-1686
    • Schapire, R.E.1    Freund, Y.2    Bartlett, P.3    Lee, W.4
  • 27
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • L. Breiman, "Arcing classifiers," Annals Statist., vol. 26, no. 3, pp. 801-849, 1998.
    • (1998) Annals Statist. , vol.26 , Issue.3 , pp. 801-849
    • Breiman, L.1
  • 28
    • 0031361611 scopus 로고    scopus 로고
    • Machine learning research: Four current directions
    • T. G. Dietterich, "Machine learning research: Four current directions," Artificial Intell. Mag., vol. 18, no. 4, pp. 97-136, 1997.
    • (1997) Artificial Intell. Mag. , vol.18 , Issue.4 , pp. 97-136
    • Dietterich, T.G.1
  • 29
    • 0000926506 scopus 로고
    • When networks disagree: Ensemble methods for hybrid neural networks
    • R. J. Mammone, Ed. London, U.K.: Chapman & Hall
    • M. P. Perrone and L. N. Cooper, "When networks disagree: Ensemble methods for hybrid neural networks," in Artificial Neural Networks for Speech and Vision, R. J. Mammone, Ed. London, U.K.: Chapman & Hall, 1993, pp. 126-142.
    • (1993) Artificial Neural Networks for Speech and Vision , pp. 126-142
    • Perrone, M.P.1    Cooper, L.N.2
  • 30
    • 0031171679 scopus 로고    scopus 로고
    • Optimal linear combinations of neural networks
    • S. Hashem, "Optimal linear combinations of neural networks," Neural Comput., vol. 10, pp. 599-614, 1997.
    • (1997) Neural Comput. , vol.10 , pp. 599-614
    • Hashem, S.1
  • 33
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • L. Breiman, "Bagging predictors," Machine Learning, vol. 24, no. 2, pp. 123-140, 1996.
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 34
    • 0000262562 scopus 로고
    • Hierarchical mixture of experts and the em algorithm
    • M. I. Jordan and R. A. Jacobs, "Hierarchical mixture of experts and the EM algorithm," Neural Comput., vol. 6, pp. 181-214, 1994.
    • (1994) Neural Comput. , vol.6 , pp. 181-214
    • Jordan, M.I.1    Jacobs, R.A.2
  • 35
    • 0029372769 scopus 로고
    • Methods for combining experts probability assessment
    • R. A. Jacobs, "Methods for combining experts probability assessment," Neural Comput., vol. 7, pp. 867-888, 1995.
    • (1995) Neural Comput. , vol.7 , pp. 867-888
    • Jacobs, R.A.1
  • 36
    • 0001920992 scopus 로고    scopus 로고
    • Human expert-level performance on a scientific image analysis task by a system using combined artificial neural networks
    • P. Chan, Ed.
    • K. J. Cherkauker, "Human expert-level performance on a scientific image analysis task by a system using combined artificial neural networks," in Working Notes AAAI Workshop Integrating Multiple Learned Models, P. Chan, Ed., 1996, pp. 15-21.
    • (1996) Working Notes AAAI Workshop Integrating Multiple Learned Models , pp. 15-21
    • Cherkauker, K.J.1
  • 39
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • R. E. Schapire, "The strength of weak learnability," Mach. Learn., vol. 5, no. 2, pp. 197-227, 1990.
    • (1990) Mach. Learn. , vol.5 , Issue.2 , pp. 197-227
    • Schapire, R.E.1
  • 40
    • 58149321460 scopus 로고
    • Boosting a weak learning algorithm by majority
    • Y. Freund, "Boosting a weak learning algorithm by majority," Inform. Comput., vol. 121, no. 2, pp. 256-285, 1995.
    • (1995) Inform. Comput. , vol.121 , Issue.2 , pp. 256-285
    • Freund, Y.1
  • 41
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Y. Freund and R. E. Schapire, "A decision-theoretic generalization of on-line learning and an application to boosting," J. Comput. Syst. Sci., vol. 55, no. 1, pp. 119-139, 1997.
    • (1997) J. Comput. Syst. Sci. , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 44
    • 0000040021 scopus 로고    scopus 로고
    • Using output codes to boost multiclass learning problems
    • San Mateo, CA: Morgan Kaufmann
    • R. E. Schapire, "Using output codes to boost multiclass learning problems," in Proc. Fourteenth Int. Conf. Machine Learning. San Mateo, CA: Morgan Kaufmann, 1997, pp. 313-321.
    • (1997) Proc. Fourteenth Int. Conf. Machine Learning , pp. 313-321
    • Schapire, R.E.1
  • 45
    • 0000551189 scopus 로고    scopus 로고
    • Popular ensemble methods: An empirical study
    • D. Opitz and R. Maclin, "Popular ensemble methods: An empirical study," J. Artif. Intell., vol. 11, pp. 169-198, 1999.
    • (1999) J. Artif. Intell. , vol.11 , pp. 169-198
    • Opitz, D.1    Maclin, R.2
  • 46
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting and randomization
    • T. Dietterich, "An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting and randomization," Mach. Learn., vol. 40, pp. 139-157, 2000.
    • (2000) Mach. Learn. , vol.40 , pp. 139-157
    • Dietterich, T.1
  • 48
    • 0029183827 scopus 로고
    • Efficient classification for multiclass problems using modular neural networks
    • R. Anand, G. Mehrotra, C. K. Mohan, and S. Ranka, "Efficient classification for multiclass problems using modular neural networks," IEEE Trans. Neural Networks, vol. 6, pp. 117-124, 1995.
    • (1995) IEEE Trans. Neural Networks , vol.6 , pp. 117-124
    • Anand, R.1    Mehrotra, G.2    Mohan, C.K.3    Ranka, S.4
  • 49
    • 0000406788 scopus 로고
    • Solving multiclass learning problems via error-correcting output codes
    • T. Dietterich and O. Bakiri, "Solving multiclass learning problems via error-correcting output codes," J. Artif. Intell. Res., no. 2, pp. 263-286, 1995.
    • (1995) J. Artif. Intell. Res. , Issue.2 , pp. 263-286
    • Dietterich, T.1    Bakiri, O.2
  • 50
    • 0002450488 scopus 로고    scopus 로고
    • Improved pairwise coupling classifiers with correcting classifiers
    • Chemnitz, Germany, Apr.
    • M. Moreira and E. Mayoraz, "Improved pairwise coupling classifiers with correcting classifiers," in Tenth Eur. Conf. Machine Learning, Chemnitz, Germany, Apr. 1998.
    • (1998) Tenth Eur. Conf. Machine Learning
    • Moreira, M.1    Mayoraz, E.2
  • 51
    • 0035914560 scopus 로고    scopus 로고
    • Decompositive classification models for electronic noses
    • M. Pardo, G. Sberveglieri, F. Masulli, and G. Valentini, "Decompositive classification models for electronic noses," Anal. Chim. Acta, vol. 446, pp. 223-232, 2001.
    • (2001) Anal. Chim. Acta , vol.446 , pp. 223-232
    • Pardo, M.1    Sberveglieri, G.2    Masulli, F.3    Valentini, G.4
  • 52
    • 84867071286 scopus 로고    scopus 로고
    • Effectiveness of error correcting output codes in multiclass learning problems
    • Cagliari, Italy: Springer-Verlag
    • F. Masulli and G. Valentini, "Effectiveness of error correcting output codes in multiclass learning problems," in Multiple Classifier Syst. First Int. Workshop, MCS 2000. Cagliari, Italy: Springer-Verlag, 2000, pp. 107-116.
    • (2000) Multiple Classifier Syst. First Int. Workshop, MCS 2000 , pp. 107-116
    • Masulli, F.1    Valentini, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.