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Volumn 33, Issue 12, 2012, Pages 1580-1586

Dynamic Random Forests

Author keywords

Dynamic induction; Ensemble of classifiers; Random feature selection; Random forests

Indexed keywords

BOOSTING ALGORITHM; ENSEMBLE OF CLASSIFIERS; INDUCTION ALGORITHMS; RANDOM FORESTS; RANDOMIZATION PROCESS; RESAMPLING; RF INDUCTION; TRAINING DATA; TREE INDUCTION;

EID: 84862295459     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2012.04.003     Document Type: Article
Times cited : (112)

References (37)
  • 1
    • 0001492549 scopus 로고    scopus 로고
    • Shape quantization and recognition with randomized trees
    • Y. Amit, and D. Geman Shape quantization and recognition with randomized trees Neural Comput. 9 1996 1545 1588
    • (1996) Neural Comput. , vol.9 , pp. 1545-1588
    • Amit, Y.1    Geman, D.2
  • 5
    • 53049101306 scopus 로고    scopus 로고
    • Forest-RK: A new random forest induction method
    • D.-S. Huang, D.C.W. II, D.S. Levine, K.-H. Jo, Lecture Notes in Computer Science Springer
    • S. Bernard, L. Heutte, and S. Adam Forest-RK: A new random forest induction method D.-S. Huang, D.C.W. II, D.S. Levine, K.-H. Jo, Proc. of the Internat. Conf. on Intelligent Computing (ICIC'08) Lecture Notes in Computer Science 5227 2008 Springer 430 437
    • (2008) Proc. of the Internat. Conf. on Intelligent Computing (ICIC'08) , vol.5227 , pp. 430-437
    • Bernard, S.1    Heutte, L.2    Adam, S.3
  • 9
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • L. Breiman Bagging predictors Mach. Learning 24 2 1996 123 140
    • (1996) Mach. Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 11
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • L. Breiman Arcing classifiers Ann. Statist. 26 3 1998 801 849
    • (1998) Ann. Statist. , vol.26 , Issue.3 , pp. 801-849
    • Breiman, L.1
  • 12
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman Random forests Mach. Learning 45 1 2001 5 32
    • (2001) Mach. Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 13
    • 34147188557 scopus 로고    scopus 로고
    • A two-stage outlier rejection strategy for numerical field extraction in handwritten documents
    • Honk Kong, China
    • Chatelain, C.; Heutte, L.; Paquet, T.; 2006. A two-stage outlier rejection strategy for numerical field extraction in handwritten documents. In: Internat. Conf. on Pattern Recognition, Honk Kong, China, vol 3, pp. 224-227.
    • (2006) Internat. Conf. on Pattern Recognition , vol.3 , pp. 224-227
    • Chatelain, C.1    Heutte, L.2    Paquet, T.3
  • 15
    • 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. Learning 40 1998 139 157
    • (1998) Mach. Learning , vol.40 , pp. 139-157
    • Dietterich, T.1
  • 21
    • 84945969217 scopus 로고    scopus 로고
    • Comparison of genetic algorithm and sequential search methods for classifier subset selection
    • Hao, H.; Liu, C.; Sako H.; 2003. Comparison of genetic algorithm and sequential search methods for classifier subset selection, In: Seventh Internat. Conf. on Document Analysis and Recognition, vol. 2, pp. 765-769.
    • (2003) Seventh Internat. Conf. on Document Analysis and Recognition , vol.2 , pp. 765-769
    • Hao, H.1    Liu, C.2    Sako, H.3
  • 22
    • 0032068263 scopus 로고    scopus 로고
    • A structural/statistical feature based vector for handwritten character recognition
    • L. Heutte, T. Paquet, J. Moreau, Y. Lecourtier, and C. Olivier A structural/statistical feature based vector for handwritten character recognition Pattern Recognition Lett. 19 7 1998 629 641
    • (1998) Pattern Recognition Lett. , vol.19 , Issue.7 , pp. 629-641
    • Heutte, L.1    Paquet, T.2    Moreau, J.3    Lecourtier, Y.4    Olivier, C.5
  • 23
    • 0032139235 scopus 로고    scopus 로고
    • The random subspace method for constructing decision forests
    • T. Ho The random subspace method for constructing decision forests IEEE Trans. Pattern Anal. Machine Intell. 20 8 1998 832 844
    • (1998) IEEE Trans. Pattern Anal. Machine Intell. , vol.20 , Issue.8 , pp. 832-844
    • Ho, T.1
  • 24
    • 0028461056 scopus 로고
    • A lexicon directed algorithm for recognition of unconstrained handwritten words
    • F. Kimura, S. Tsuruoka, Y. Miyake, and M. Shridhar A lexicon directed algorithm for recognition of unconstrained handwritten words IEICE Trans. Inform. Syst. E77-D 7 1994 785 793
    • (1994) IEICE Trans. Inform. Syst. , vol.E77-D , Issue.7 , pp. 785-793
    • Kimura, F.1    Tsuruoka, S.2    Miyake, Y.3    Shridhar, M.4
  • 26
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner Gradient-based learning applied to document recognition Proc. IEEE 86 11 1998 2278 2324
    • (1998) Proc. IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • Lecun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 27
    • 41549131613 scopus 로고    scopus 로고
    • Evidence contrary to the statistical view of boosting
    • D. Mease, and A. Wyner Evidence contrary to the statistical view of boosting J. Mach. Learn. Res. 9 2008 131 156
    • (2008) J. Mach. Learn. Res. , vol.9 , pp. 131-156
    • Mease, D.1    Wyner, A.2
  • 28
    • 35248862907 scopus 로고    scopus 로고
    • An introduction to boosting and leveraging
    • R. Meir, and G. Rätsch An introduction to boosting and leveraging Adv. Lect. Machine Learn. 2003 118 183
    • (2003) Adv. Lect. Machine Learn. , pp. 118-183
    • Meir, R.1    Rätsch, G.2
  • 29
    • 82255174148 scopus 로고    scopus 로고
    • On the stability and ranking of predictors from random forest variable importance measures
    • K.K. Nicodemus On the stability and ranking of predictors from random forest variable importance measures Briefings Bioinform. 12 4 2011 369 373
    • (2011) Briefings Bioinform. , vol.12 , Issue.4 , pp. 369-373
    • Nicodemus, K.K.1
  • 32
    • 33847096395 scopus 로고    scopus 로고
    • Bias in random forest variable importance measures: Illustrations, sources and a solution
    • C. Strobl, A.L. Boulesteix, A. Zeileis, and T. Hothorn Bias in random forest variable importance measures: Illustrations, sources and a solution BMC Bioinform. 8 25 2007
    • (2007) BMC Bioinform. , vol.8 , Issue.25
    • Strobl, C.1    Boulesteix, A.L.2    Zeileis, A.3    Hothorn, T.4
  • 33
  • 35
    • 77958064179 scopus 로고    scopus 로고
    • Mining data with random forests: A survey and results of new tests
    • A. Verikas, A. Gelzinis, and M. Bacauskiene Mining data with random forests: A survey and results of new tests Pattern Recognition 44 2 2011 330 349
    • (2011) Pattern Recognition , vol.44 , Issue.2 , pp. 330-349
    • Verikas, A.1    Gelzinis, A.2    Bacauskiene, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.