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Volumn 3077, Issue , 2004, Pages 263-272

Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias-Variance Analysis

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; PROBABILITY DISTRIBUTIONS; SUPPORT VECTOR MACHINES;

EID: 35048868343     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-25966-4_26     Document Type: Article
Times cited : (8)

References (15)
  • 1
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman, L.: Bagging predictors. Machine Learning 24 (1996) 123-140
    • (1996) Machine Learning , vol.24 , pp. 123-140
    • Breiman, L.1
  • 2
    • 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. Machine Learning 40 (2000) 139-158
    • (2000) Machine Learning , vol.40 , pp. 139-158
    • Dietterich, T.1
  • 4
    • 26944501740 scopus 로고    scopus 로고
    • Bias-variance analysis of Support Vector Machines for the development of SVM-based ensemble methods
    • accepted for publication
    • Valentini, G., Dietterich, T.G.: Bias-variance analysis of Support Vector Machines for the development of SVM-based ensemble methods. Journal of Machine Learning Research (accepted for publication)
    • Journal of Machine Learning Research
    • Valentini, G.1    Dietterich, T.G.2
  • 5
    • 84947560298 scopus 로고    scopus 로고
    • Bias-variance analysis and ensembles of SVM
    • MCS2002, Cagliari, Italy. Springer-Verlag
    • Valentini, G., Dietterich, T.: Bias-variance analysis and ensembles of SVM. In: MCS2002, Cagliari, Italy. Vol. 2364 of Lecture Notes in Computer Science., Springer-Verlag (2002) 222-231
    • (2002) Lecture Notes in Computer Science , vol.2364 , pp. 222-231
    • Valentini, G.1    Dietterich, T.2
  • 7
    • 1942418086 scopus 로고    scopus 로고
    • Pattern Classification Using Support Vector Machine Ensemble
    • IEEE
    • Kim, H., Pang, S., Je, H., Kim, D., Bang, S.: Pattern Classification Using Support Vector Machine Ensemble. In: Proc. of ICPR'02. Vol. 2., IEEE (2002) 20160-20163
    • (2002) Proc. of ICPR'02. , vol.2 , pp. 20160-20163
    • Kim, H.1    Pang, S.2    Je, H.3    Kim, D.4    Bang, S.5
  • 8
    • 0032634129 scopus 로고    scopus 로고
    • Pasting Small Votes for Classification in Large Databases and On-Line
    • Breiman, L.: Pasting Small Votes for Classification in Large Databases and On-Line. Machine Learning 36 (1999) 85-103
    • (1999) Machine Learning , vol.36 , pp. 85-103
    • Breiman, L.1
  • 9
    • 0002714543 scopus 로고    scopus 로고
    • Making large scale SVM learning practical
    • Scholkopf B., Burges C., S.A., ed.: MIT Press, Cambridge, MA
    • Joachims, T.: Making large scale SVM learning practical. In Scholkopf B., Burges C., S.A., ed.: Advances in Kernel Methods - Support Vector Learning. MIT Press, Cambridge, MA (1999) 169-184
    • (1999) Advances in Kernel Methods - Support Vector Learning , pp. 169-184
    • Joachims, T.1
  • 11
    • 29144512925 scopus 로고    scopus 로고
    • PhD thesis, DISI, Università di Genova, Italy ftp://ftp.disi. unige.it/person/ValentiniG/Tesi/finalversion/vale-th-2003-04.pdf
    • Valentini, G.: Ensemble methods based on bias-variance analysis. PhD thesis, DISI, Università di Genova, Italy (2003), ftp://ftp.disi.unige. it/person/ValentiniG/Tesi/finalversion/vale-th-2003-04.pdf.
    • (2003) Ensemble Methods Based on Bias-variance Analysis
    • Valentini, G.1
  • 13
    • 0036825897 scopus 로고    scopus 로고
    • NEURObjects: An object-oriented library for neural network development
    • Valentini, G., Masulli, F.: NEURObjects: an object-oriented library for neural network development. Neurocomputing 48 (2002) 623-646
    • (2002) Neurocomputing , vol.48 , pp. 623-646
    • Valentini, G.1    Masulli, F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.