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Volumn 75, Issue 1, 2013, Pages 55-80

Variable selection with error control: Another look at stability selection

Author keywords

Complementary pairs stability selection; R concavity; Subagging; Subsampling; Variable selection

Indexed keywords


EID: 84871371181     PISSN: 13697412     EISSN: 14679868     Source Type: Journal    
DOI: 10.1111/j.1467-9868.2011.01034.x     Document Type: Article
Times cited : (287)

References (29)
  • 1
    • 0033536012 scopus 로고    scopus 로고
    • Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
    • Alon, U., Barkai, N., Notterman, D. A., Gish, K., Ybarra, S., Mack, D. and Levine, A. J. (1999) Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc. Natn. Acad. Sci. USA, 96, 6745-6750.
    • (1999) Proc. Natn. Acad. Sci. USA , vol.96 , pp. 6745-6750
    • Alon, U.1    Barkai, N.2    Notterman, D.A.3    Gish, K.4    Ybarra, S.5    Mack, D.6    Levine, A.J.7
  • 3
    • 56449120785 scopus 로고    scopus 로고
    • Bolasso: model consistent lasso estimation through the bootstrap
    • New York: Association for Computing Machinery.
    • Bach, F. (2008) Bolasso: model consistent lasso estimation through the bootstrap. In Proc. 25th Int. Conf. Machine Learning, pp. 33-40. New York: Association for Computing Machinery.
    • (2008) Proc. 25th Int. Conf. Machine Learning , pp. 33-40
    • Bach, F.1
  • 4
    • 77949521444 scopus 로고    scopus 로고
    • On the rate of convergence of the bagged nearest neighbor estimate
    • Biau, G., Cérou, F. and Guyader, A. (2010) On the rate of convergence of the bagged nearest neighbor estimate. J. Mach. Learn. Res., 11, 687-712.
    • (2010) J. Mach. Learn. Res. , vol.11 , pp. 687-712
    • Biau, G.1    Cérou, F.2    Guyader, A.3
  • 5
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman, L. (1996) Bagging predictors. Mach. Learn., 24, 123-140.
    • (1996) Mach. Learn. , vol.24 , pp. 123-140
    • Breiman, L.1
  • 6
    • 84871368074 scopus 로고    scopus 로고
    • Using adaptive bagging to debias regressions. Technical Report Department of Statistics, University of California, Berkeley.
    • Breiman, L. (1999) Using adaptive bagging to debias regressions. Technical Report Department of Statistics, University of California, Berkeley.
    • (1999)
    • Breiman, L.1
  • 7
    • 0043289776 scopus 로고    scopus 로고
    • Analyzing bagging
    • Bühlmann, P. and Yu, B. (2002) Analyzing bagging. Ann. Statist., 30, 927-961.
    • (2002) Ann. Statist. , vol.30 , pp. 927-961
    • Bühlmann, P.1    Yu, B.2
  • 8
    • 84871658599 scopus 로고    scopus 로고
    • Maximum likelihood estimation of a multi-dimensional log-concave density (with discussion)
    • Cule, M., Samworth, R. and Stewart, M. (2010) Maximum likelihood estimation of a multi-dimensional log-concave density (with discussion). J. R. Statist. Soc. B, 72, 545-607.
    • (2010) J. R. Statist. Soc. B , vol.72 , pp. 545-607
    • Cule, M.1    Samworth, R.2    Stewart, M.3
  • 10
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • Dudoit, S., Fridlyand, J. and Speed, T. P. (2002) Comparison of discrimination methods for the classification of tumors using gene expression data. J. Am. Statist. Ass., 97, 77-87.
    • (2002) J. Am. Statist. Ass. , vol.97 , pp. 77-87
    • Dudoit, S.1    Fridlyand, J.2    Speed, T.P.3
  • 11
    • 62749189131 scopus 로고    scopus 로고
    • Maximum likelihood estimation of a log-concave density and its distribution function: basic properties and uniform consistency
    • Dümbgen, L. and Rufibach, K. (2009) Maximum likelihood estimation of a log-concave density and its distribution function: basic properties and uniform consistency. Bernoulli, 15, 40-68.
    • (2009) Bernoulli , vol.15 , pp. 40-68
    • Dümbgen, L.1    Rufibach, K.2
  • 13
    • 77949352853 scopus 로고    scopus 로고
    • A selective overview of variable selection in high dimensional feature space
    • Fan, J. and Lv, J. (2010) A selective overview of variable selection in high dimensional feature space. Statist. Sin., 20, 101-148.
    • (2010) Statist. Sin. , vol.20 , pp. 101-148
    • Fan, J.1    Lv, J.2
  • 14
    • 70449440300 scopus 로고    scopus 로고
    • Ultrahigh dimensional feature selection: beyond the linear model
    • Fan, J., Samworth, R. and Wu, Y. (2009) Ultrahigh dimensional feature selection: beyond the linear model. J. Mach. Learn. Res., 10, 2013-2038.
    • (2009) J. Mach. Learn. Res. , vol.10 , pp. 2013-2038
    • Fan, J.1    Samworth, R.2    Wu, Y.3
  • 15
    • 77950537175 scopus 로고    scopus 로고
    • Regularization paths for generalized linear models via coordinate descent
    • Friedman, J., Hastie, T. and Tibshirani, R. (2010) Regularization paths for generalized linear models via coordinate descent. J. Statist. Softwr., 33, 1-22.
    • (2010) J. Statist. Softwr. , vol.33 , pp. 1-22
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 16
    • 20744442569 scopus 로고    scopus 로고
    • Properties of bagged nearest neighbour classifiers
    • Hall, P. and Samworth, R. J. (2005) Properties of bagged nearest neighbour classifiers. J. R. Statist. Soc. B, 67, 363-379.
    • (2005) J. R. Statist. Soc. B , vol.67 , pp. 363-379
    • Hall, P.1    Samworth, R.J.2
  • 17
    • 79951748752 scopus 로고    scopus 로고
    • A variance reduction framework for stable feature selection
    • Sydney: Institute of Electrical and Electronics Engineers Computer Society.
    • Han, Y. and Yu, L. (2010) A variance reduction framework for stable feature selection. In Proc. 10th Int. Conf. Data Mining, pp. 206-215. Sydney: Institute of Electrical and Electronics Engineers Computer Society.
    • (2010) Proc. 10th Int. Conf. Data Mining , pp. 206-215
    • Han, Y.1    Yu, L.2
  • 18
    • 34248647608 scopus 로고    scopus 로고
    • Stability of feature selection algorithms: a study on high-dimensional spaces
    • Kalousis, A., Prados, J. and Hilario, M. (2007) Stability of feature selection algorithms: a study on high-dimensional spaces. Knowl. Inform. Syst., 12, 95-116.
    • (2007) Knowl. Inform. Syst. , vol.12 , pp. 95-116
    • Kalousis, A.1    Prados, J.2    Hilario, M.3
  • 19
    • 77957585646 scopus 로고    scopus 로고
    • Quasi-concave density estimation
    • Koenker, R. and Mizera, I. (2010) Quasi-concave density estimation. Ann. Statist., 38, 2998-3027.
    • (2010) Ann. Statist. , vol.38 , pp. 2998-3027
    • Koenker, R.1    Mizera, I.2
  • 21
    • 84898963992 scopus 로고    scopus 로고
    • Stability-based model selection
    • (eds S. Becker, S. Thrun and K. Obermayer) Cambridge: MIT Press
    • Lange, T., Braun, M., Roth, V. and Buhmann, J. (2003) Stability-based model selection. In Advances in Neural Information Processing Systems, vol. 15 (eds S. Becker, S. Thrun and K. Obermayer ), pp. 617-624. Cambridge: MIT Press.
    • (2003) Advances in Neural Information Processing Systems , vol.15 , pp. 617-624
    • Lange, T.1    Braun, M.2    Roth, V.3    Buhmann, J.4
  • 22
    • 70350686854 scopus 로고    scopus 로고
    • Consensus group based stable feature selection
    • New York: Association for Computing Machinery.
    • Loscalzo, S. Yu, L. and Ding, C. (2009) Consensus group based stable feature selection. In Proc. 15th Int. Conf. Knowledge Discovery and Data Mining, pp. 567-576. New York: Association for Computing Machinery.
    • (2009) Proc. 15th Int. Conf. Knowledge Discovery and Data Mining , pp. 567-576
    • Loscalzo, S.1    Yu, L.2    Ding, C.3
  • 23
  • 24
    • 79951480123 scopus 로고    scopus 로고
    • R Development Core Team Vienna: R Foundation for Statistical Computing.
    • R Development Core Team (2010) R: a Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.
    • (2010) R: a Language and Environment for Statistical Computing
  • 25
    • 56049119676 scopus 로고    scopus 로고
    • Robust feature selection using ensemble feature selection techniques
    • Berlin: Springer.
    • Saeys, Y. Abeel, T. and Peer, Y. V. (2008) Robust feature selection using ensemble feature selection techniques. In Proc. Eur. Conf. Machine Learning., pp. 313-325. Berlin: Springer.
    • (2008) Proc. Eur. Conf. Machine Learning. , pp. 313-325
    • Saeys, Y.1    Abeel, T.2    Peer, Y.V.3
  • 26
    • 84871372633 scopus 로고    scopus 로고
    • Optimal weighted nearest neighbour classifiers. Arxiv Preprint. (Available from
    • Samworth, R. J. (2011) Optimal weighted nearest neighbour classifiers. Arxiv Preprint. (Available from http://arxiv.org/pdf/1101.5783
    • (2011)
    • Samworth, R.J.1
  • 27
    • 78650124411 scopus 로고    scopus 로고
    • Nonparametric estimation of convex-transformed densities
    • Seregin, A. and Wellner, J. A. (2010) Nonparametric estimation of convex-transformed densities. Ann. Statist., 38, 3751-3781.
    • (2010) Ann. Statist. , vol.38 , pp. 3751-3781
    • Seregin, A.1    Wellner, J.A.2
  • 28
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. J. R. Statist. Soc. B, 58, 267-288.
    • (1996) J. R. Statist. Soc. B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 29
    • 0035998823 scopus 로고    scopus 로고
    • Detecting the presence of mixing with multiscale maximum likelihood
    • Walther, G. (2002) Detecting the presence of mixing with multiscale maximum likelihood. J. Am. Statist. Ass., 97, 508-513.
    • (2002) J. Am. Statist. Ass. , vol.97 , pp. 508-513
    • Walther, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.