메뉴 건너뛰기




Volumn 10, Issue , 2009, Pages 2013-2038

Ultrahigh Dimensional Feature Selection: Beyond the Linear Model

Author keywords

Classification; Feature screening; Feature selection; Generalized linear models; Robust regression

Indexed keywords

CLASSIFICATION; FEATURE SCREENING; FEATURE SELECTION; GENERALIZED LINEAR MODELS; ROBUST REGRESSION;

EID: 70449440300     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (412)

References (46)
  • 1
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • Hirotsugu Akaike. A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6):716-723, 1974.
    • (1974) IEEE Transactions on Automatic Control , vol.19 , Issue.6 , pp. 716-723
    • Akaike, H.1
  • 2
    • 0028496468 scopus 로고
    • Diettrich. Learning boolean concepts in the presence of many irrelevant features
    • Hussein Almuallim and Thomas G. Diettrich. Learning boolean concepts in the presence of many irrelevant features. Artificial Intelligence, 69(1-2):279-305, 1994.
    • (1994) Artificial Intelligence , vol.69 , Issue.1-2 , pp. 279-305
    • Almuallim, H.1    Thomas, G.2
  • 3
    • 0442312210 scopus 로고    scopus 로고
    • Regularized wavelet approximations (with discussion)
    • Anestis Antoniadis and Jianqing Fan. Regularized wavelet approximations (with discussion). J. Amer. Statist. Assoc., 96(455):939-967, 2001.
    • (2001) J. Amer. Statist. Assoc. , vol.96 , Issue.455 , pp. 939-967
    • Antoniadis, A.1    Fan, J.2
  • 4
    • 33645527646 scopus 로고    scopus 로고
    • Prediction by supervised principal components
    • Eric Bair, Trevor Hastie, Debashis Paul and Robert Tibshirani. Prediction by supervised principal components. J. Amer. Statist. Assoc., 101(473):119-137, 2006.
    • (2006) J. Amer. Statist. Assoc. , vol.101 , Issue.473 , pp. 119-137
    • Bair, E.1    Hastie, T.2    Paul, D.3    Tibshirani, R.4
  • 5
    • 2942731013 scopus 로고    scopus 로고
    • Extensions to metric based model selection
    • Yoshua Bengio and Nicolas Chapados. Extensions to metric based model selection. J. Mach. Learn. Res., 3:1209-1227, 2003.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1209-1227
    • Bengio, Y.1    Chapados, N.2
  • 7
    • 68649086910 scopus 로고    scopus 로고
    • Simultaneous analysis of Lasso and Dantzig selector
    • Peter J. Bickel, Ya'acov Ritov and Alexandre Tsybakov. Simultaneous analysis of Lasso and Dantzig selector. Ann. Statist., 37(4):1705-1732, 2009.
    • (2009) Ann. Statist. , vol.37 , Issue.4 , pp. 1705-1732
    • Bickel, P.J.1    Ritov, Y.2    Tsybakov, A.3
  • 8
    • 34548275795 scopus 로고    scopus 로고
    • The Dantzig selector: Statistical estimation when p is much larger than n (with discussion)
    • Emmanuel Candes and Terrence Tao. The Dantzig selector: statistical estimation when p is much larger than n (with discussion). Ann. Statist., 35(6):2313-2404, 2007.
    • (2007) Ann. Statist. , vol.35 , Issue.6 , pp. 2313-2404
    • Candes, E.1    Tao, T.2
  • 10
    • 0043203327 scopus 로고    scopus 로고
    • Boldrick. Multiple hypothesis testing in microarray experiments
    • Sandrine Dudoit, Juliet P. Shaffer and Jennifer C. Boldrick. Multiple hypothesis testing in microarray experiments. Statist. Sci., 18:71-103, 2003.
    • (2003) Statist. Sci. , vol.18 , pp. 71-103
    • Dudoit, S.1    Shaffer, J.P.2    Jennifer, C.3
  • 12
    • 47749152434 scopus 로고    scopus 로고
    • Microarrays, empirical Bayes and the two-groups model (with discussion)
    • Bradley Efron. Microarrays, empirical Bayes and the two-groups model (with discussion). Statist. Sci., 23:1-47, 2008.
    • (2008) Statist. Sci. , vol.23 , pp. 1-47
    • Efron, B.1
  • 13
    • 53849089038 scopus 로고    scopus 로고
    • High dimensional classification using shrunken independence rule
    • Jianqing Fan and Yingying Fan. High dimensional classification using shrunken independence rule. Ann. Statist, 36(6):3605-12637, 2008.
    • (2008) Ann. Statist , vol.36 , Issue.6 , pp. 3605-12637
    • Fan, J.1    Fan, Y.2
  • 14
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • Jianqing Fan and Runze Li. Variable selection via nonconcave penalized likelihood and its oracle properties. J. Amer. Statist. Assoc., 96:1348-1360, 2001.
    • (2001) J. Amer. Statist. Assoc. , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 15
    • 53849086824 scopus 로고    scopus 로고
    • Sure independence screening for ultra-high dimensional feature space (with discussion)
    • Jianqing Fan and Jinchi Lv. Sure independence screening for ultra-high dimensional feature space (with discussion). J. Roy. Statist. Soe, Ser. B, 70:849-911, 2008.
    • (2008) J. Roy. Statist. Soe, Ser. B , vol.70 , pp. 849-911
    • Fan, J.1    Lv, J.2
  • 16
    • 24344502730 scopus 로고    scopus 로고
    • On non-concave penalized likelihood with diverging number of parameters
    • Jianqing Fan and Heng Peng. On non-concave penalized likelihood with diverging number of parameters. Ann. Statist., 32(3):928-961, 2004.
    • (2004) Ann. Statist. , vol.32 , Issue.3 , pp. 928-961
    • Fan, J.1    Peng, H.2
  • 17
    • 33748041130 scopus 로고    scopus 로고
    • Statistical analysis of DNA microarray data
    • Jianqing Fan and Yi Ren. Statistical analysis of DNA microarray data. Clinical Cancer Res., 12:4469-4473, 2006.
    • (2006) Clinical Cancer Res. , vol.12 , pp. 4469-4473
    • Fan, J.1    Ren, Y.2
  • 18
    • 70449391346 scopus 로고    scopus 로고
    • Sure Independence Screening in Generalized Linear Models with NPDimensionality
    • Jianqing Fan and Rui Song. Sure Independence Screening in Generalized Linear Models with NPDimensionality. Manuscript, 2009.
    • (2009) Manuscript
    • Fan, J.1    Song, R.2
  • 19
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Yoav Freund, and Robert E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. System Sci., 55(1): 119-139.
    • J. Comput. System Sci. , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 20
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Isabelle Guyon and André Elisseeff. An introduction to variable and feature selection. J. Mach. Learn. Res., 3:1157-1182, 2003.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 21
    • 33745891586 scopus 로고    scopus 로고
    • Isabelle Guyon, Steve Gunn, Masoud Nikravesh and Lofti Zadeh, editors. Springer, New York
    • Isabelle Guyon, Steve Gunn, Masoud Nikravesh and Lofti Zadeh, editors. Feature Extraction, Foundations and Applications. Springer, New York, 2006.
    • (2006) Feature Extraction, Foundations and Applications.
  • 22
    • 85065703189 scopus 로고    scopus 로고
    • Correlation-based feature selection for discrete and numeric class machine learning
    • Stanford, CA
    • Mark A. Hall. Correlation-based feature selection for discrete and numeric class machine learning. In International Conference on Machine Learning, Stanford, CA, pages 359-366, 2000.
    • (2000) International Conference on Machine Learning , pp. 359-366
    • Hall, M.A.1
  • 23
    • 68849102598 scopus 로고    scopus 로고
    • Tiling methods for assessing the influence of components in a classifier
    • Peter Hall, D. M. Titterington, and Jing-Hao Xue. Tiling methods for assessing the influence of components in a classifier. J. Roy. Statist. Soe, Ser. B, 71(4):783-803, 2009.
    • (2009) J. Roy. Statist. Soe, Ser. B , vol.71 , Issue.4 , pp. 783-803
    • Hall, P.1    Titterington, D.M.2    Xue, J.-H.3
  • 25
    • 0003157339 scopus 로고
    • Robust estimation of location
    • Peter J. Huber. Robust estimation of location. Ann. Math. Statist., 35:73-101, 1964.
    • (1964) Ann. Math. Statist. , vol.35 , pp. 73-101
    • Huber, P.J.1
  • 27
    • 0001832882 scopus 로고
    • Estimating attributes: Analysis and extension of RELIEF
    • Springer Berlin/Heidelberg
    • Igor Kononenko. Estimating attributes: Analysis and extension of RELIEF. In Machine Learning: ECML-94, Springer Berlin/Heidelberg, 1994.
    • (1994) Machine Learning: ECML-94
    • Kononenko, I.1
  • 28
    • 2142775432 scopus 로고    scopus 로고
    • Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data
    • Yoonkyung Lee, Yi Lin and Grace Wahba. Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data. J. Amer. Statist. Assoc., 99(465):67-81, 2004.
    • (2004) J. Amer. Statist. Assoc. , vol.99 , Issue.465 , pp. 67-81
    • Lee, Y.1    Lin, Y.2    Wahba, G.3
  • 30
    • 15944365213 scopus 로고    scopus 로고
    • Multicategory Ψ-learning and support vector machine: Computational tools
    • Yufeng Liu, Xiaotong Shen and Hani Doss. Multicategory Ψ-learning and support vector machine: computational tools. J. Computat. Graph. Statist., 14(1):219-236, 2005.
    • (2005) J. Computat. Graph. Statist. , vol.14 , Issue.1 , pp. 219-236
    • Liu, Y.1    Shen, X.2    Doss, H.3
  • 32
    • 33747163541 scopus 로고    scopus 로고
    • High dimensional graphs and variable selection with the Lasso
    • Nicolai Meinshausen and Peter Bühlmann. High dimensional graphs and variable selection with the Lasso. The Annals of Statistics, 34(3): 1436-1462, 2006.
    • (2006) The Annals of Statistics , vol.34 , Issue.3 , pp. 1436-1462
    • Meinshausen, N.1    Bühlmann, P.2
  • 34
    • 34547849507 scopus 로고    scopus 로고
    • 1-regularization path algorithm for generalized linear models
    • 1-regularization path algorithm for generalized linear models. J. Roy. Statist. Soe Ser. B, 69(4):659-677, 2007.
    • (2007) J. Roy. Statist. Soe Ser. B , vol.69 , Issue.4 , pp. 659-677
    • Park, M.Y.1    Hastie, T.2
  • 35
    • 51049112528 scopus 로고    scopus 로고
    • "Pre-conditioning" for feature selection and regression in high-dimensional problems
    • Debashis Paul, Eric Bair, Trevor Hastie and Robert Tibshirani. "Pre-conditioning" for feature selection and regression in high-dimensional problems. Ann. Statist., 36(4): 1595-1618.
    • Ann. Statist. , vol.36 , Issue.4 , pp. 1595-1618
    • Paul, D.1    Bair, E.2    Hastie, T.3    Tibshirani, R.4
  • 36
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Gideon Schwarz. Estimating the dimension of a model. Ann. Statist., 6(2):461-464, 1978.
    • (1978) Ann. Statist. , vol.6 , Issue.2 , pp. 461-464
    • Schwarz, G.1
  • 37
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via lasso
    • Robert Tibshirani. Regression shrinkage and selection via lasso. Jour. Roy. Statist. Soc B., 58(1):267-288, 1996.
    • (1996) Jour. Roy. Statist. Soc B. , vol.58 , Issue.1 , pp. 267-288
    • Tibshirani, R.1
  • 38
    • 2342533421 scopus 로고    scopus 로고
    • Class prediction by nearest shrunken centroids, with applications to DNA microarrays
    • Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan and Gilbert Chu. Class prediction by nearest shrunken centroids, with applications to DNA microarrays. Statist. Sci., 18(1):104-117, 2003.
    • (2003) Statist. Sci. , vol.18 , Issue.1 , pp. 104-117
    • Tibshirani, R.1    Hastie, T.2    Narasimhan, B.3    Chu, G.4
  • 40
    • 1942451938 scopus 로고    scopus 로고
    • Feature selection for high-dimensional data: A fast correlation-based filter solution
    • Washington DC, USA
    • Lei Yu and Huan Liu. Feature selection for high-dimensional data: a fast correlation-based filter solution. In International Conference on Machine Learning, pages 856-863, Washington DC, USA, 2003.
    • (2003) International Conference on Machine Learning , pp. 856-863
    • Yu, L.1    Liu, H.2
  • 41
    • 33846114377 scopus 로고    scopus 로고
    • The adaptive Lasso and its oracle properties
    • Hui Zou. The adaptive Lasso and its oracle properties. J. Amer. Statist. Assoc., 101(476): 1418-1429, 2006.
    • (2006) J. Amer. Statist. Assoc. , vol.101 , Issue.476 , pp. 1418-1429
    • Zou, H.1
  • 42
    • 70449383414 scopus 로고    scopus 로고
    • Nearly unbiased variable selection under minimax concave penalty
    • forthcoming
    • Cun-Hui Zhang. Nearly unbiased variable selection under minimax concave penalty. Ann. Statist., forthcoming.
    • Ann. Statist.
    • Zhang, C.-H.1
  • 43
    • 50949096321 scopus 로고    scopus 로고
    • The sparsity and bias of the LASSO selection in high-dimensional linear regression
    • Cun-Hui Zhang and Jian Huang. The sparsity and bias of the LASSO selection in high-dimensional linear regression. Ann. Statist., 36(4): 1567-1594.
    • Ann. Statist. , vol.36 , Issue.4 , pp. 1567-1594
    • Zhang, C.-H.1    Huang, J.2
  • 45
    • 33845263263 scopus 로고    scopus 로고
    • On model selection consistency of Lasso
    • Peng Zhao and Bin Yu. On model selection consistency of Lasso.J. Machine Learning Res., 7:2541-2563, 2006.
    • (2006) J. Machine Learning Res. , vol.7 , pp. 2541-2563
    • Zhao, P.1    Yu, B.2
  • 46
    • 51049104549 scopus 로고    scopus 로고
    • One-step sparse estimates in nonconcave penalized likelihood models (with discussion)
    • Hui Zou and Runze Li. One-step sparse estimates in nonconcave penalized likelihood models (with discussion). Ann. Statist., 36(4): 1509-1566, 2008.
    • (2008) Ann. Statist. , vol.36 , Issue.4 , pp. 1509-1566
    • Zou, H.1    Li, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.