메뉴 건너뛰기




Volumn 51, Issue 1, 2012, Pages 74-81

Probability Machines: Consistent probability estimation using nonparametric learning machines

Author keywords

Brier score; Consistency; K nearest neighbor; Logistic regression; Probability estimation; Random forest

Indexed keywords

ARTICLE; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; HUMAN; LEARNING; METHODOLOGY; NONPARAMETRIC TEST; PROBABILITY; STATISTICAL MODEL; STATISTICS;

EID: 84855764322     PISSN: 00261270     EISSN: None     Source Type: Journal    
DOI: 10.3414/ME00-01-0052     Document Type: Article
Times cited : (203)

References (36)
  • 1
    • 0033574245 scopus 로고    scopus 로고
    • Assessing the generalizability of prognostic information
    • Justice AC, Covinsky KE, Berlin JA. Assessing the generalizability of prognostic information. Ann Intern Med 1999; 130: 515-524.
    • (1999) Ann Intern Med , vol.130 , pp. 515-524
    • Justice, A.C.1    Covinsky, K.E.2    Berlin, J.A.3
  • 5
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. Bagging predictors. Mach Learn 1996; 24: 123-140.
    • (1996) Mach Learn , vol.24 , pp. 123-140
    • Breiman, L.1
  • 6
    • 0035478854 scopus 로고    scopus 로고
    • Random Forests
    • Breiman L. Random Forests. Mach Learn 2001; 45: 5-32.
    • (2001) Mach Learn , vol.45 , pp. 5-32
    • Breiman, L.1
  • 7
    • 33947284406 scopus 로고    scopus 로고
    • Boosted classification trees and class probability/quantile estimation
    • Mease D, Wyner AJ, Buja A. Boosted classification trees and class probability/quantile estimation. J Mach Learn Res 2007; 8: 409-439.
    • (2007) J Mach Learn Res , vol.8 , pp. 409-439
    • Mease, D.1    Wyner, A.J.2    Buja, A.3
  • 8
    • 41549131613 scopus 로고    scopus 로고
    • Evidence contrary to the statistical view of boosting
    • Mease D, Wyner A. Evidence contrary to the statistical view of boosting. J Mach Learn Res 2008; 9: 131-156.
    • (2008) J Mach Learn Res , vol.9 , pp. 131-156
    • Mease, D.1    Wyner, A.2
  • 9
    • 34247596518 scopus 로고    scopus 로고
    • Sparseness vs estimating conditional probabilities: Some asymptotic results
    • Bartlett PL, Tewari A. Sparseness vs estimating conditional probabilities: Some asymptotic results. J Mach Learn Res 2007; 8: 775-790.
    • (2007) J Mach Learn Res , vol.8 , pp. 775-790
    • Bartlett, P.L.1    Tewari, A.2
  • 10
    • 85162004347 scopus 로고    scopus 로고
    • Universal consistency of multi-class support vector classifiation
    • In: Lafferty J, Williams CKI, Shawe-Taylor J, Zemel RS, Culotta A, editors, West Chester: Curran Associates Inc
    • Glasmachers T. Universal consistency of multi-class support vector classifiation. In: Lafferty J, Williams CKI, Shawe-Taylor J, Zemel RS, Culotta A, editors. Advances in Neural Information Processing Systems 23. West Chester: Curran Associates Inc; 2010.pp 739-747.
    • (2010) Advances In Neural Information Processing Systems , vol.23 , pp. 739-747
    • Glasmachers, T.1
  • 11
    • 40249094631 scopus 로고    scopus 로고
    • Probability estimation for large-margin classifiers
    • Wang J, Shen X, Liu Y. Probability estimation for large-margin classifiers. Biometrika 2008; 95: 149-167.
    • (2008) Biometrika , vol.95 , pp. 149-167
    • Wang, J.1    Shen, X.2    Liu, Y.3
  • 12
    • 79955702502 scopus 로고    scopus 로고
    • LIBSVM A library for support vector machines
    • Chang C-C, Lin C-J. LIBSVM: A library for support vector machines. ACM TIST 2011; 2: 27: 21-27: 27.
    • (2011) ACM TIST , vol.2 , Issue.27 , pp. 21-27
    • Chang, C.-C.1    Lin, C-J.2
  • 13
    • 77954485448 scopus 로고    scopus 로고
    • On safari to Random Jungle: A fast implementation of Random Forests for high dimensional data
    • Schwarz DF, König IR, Ziegler A. On safari to Random Jungle: A fast implementation of Random Forests for high dimensional data. Bioinformatics 2010; 26: 1752-1758.
    • (2010) Bioinformatics , vol.26 , pp. 1752-1758
    • Schwarz, D.F.1    König, I.R.2    Ziegler, A.3
  • 15
    • 54249099241 scopus 로고    scopus 로고
    • Consistency of random forests and other averaging classifiers
    • Biau G, Devroye L, Lugosi G. Consistency of random forests and other averaging classifiers. J Mach Learn Res 2008; 9: 2039-2057.
    • (2008) J Mach Learn Res , vol.9 , pp. 2039-2057
    • Biau, G.1    Devroye, L.2    Lugosi, G.3
  • 17
    • 77956747417 scopus 로고    scopus 로고
    • On the layered nearest neigh bour estimate, the bagged nearest neighbour estimate and the random forest method in regression and classification
    • Biau G, Devroye L. On the layered nearest neigh bour estimate, the bagged nearest neighbour estimate and the random forest method in regression and classification. J Multivariate Anal 2010; 101: 2499-2518.
    • (2010) J Multivariate Anal , vol.101 , pp. 2499-2518
    • Biau, G.1    Devroye, L.2
  • 18
    • 33745653724 scopus 로고    scopus 로고
    • Random forests and adaptive nearest neighbors
    • Lin Y, Jeon Y. Random forests and adaptive nearest neighbors. J Am Stat Assoc 2006; 101: 578-590.
    • (2006) J Am Stat Assoc , vol.101 , pp. 578-590
    • Lin, Y.1    Jeon, Y.2
  • 20
    • 77949521444 scopus 로고    scopus 로고
    • On the rate of convergencez of the bagged nearest neighbor estimate
    • Biau G, Cérou F, Guyader A. On the rate of convergencez of the bagged nearest neighbor estimate. J Mach Learn Res 2010; 11: 687-712.
    • (2010) J Mach Learn Res , vol.11 , pp. 687-712
    • Biau, G.1    Cérou, F.2    Guyader, A.3
  • 21
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: A statistical view of boosting
    • Friedman J, Hastie T, Tibshirani R. Additive logistic regression: a statistical view of boosting. Ann Statist 2000; 28: 337-407.
    • (2000) Ann Statist , vol.28 , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 22
    • 0023843391 scopus 로고
    • Analysis of hidden units in a layered network trained to classify sonar targets
    • Gorman RP, Sejnowski TJ. Analysis of hidden units in a layered network trained to classify sonar targets. Neural Networks 1988; 1: 75-89.
    • (1988) Neural Networks , vol.1 , pp. 75-89
    • Gorman, R.P.1    Sejnowski, T.J.2
  • 23
    • 33947274775 scopus 로고    scopus 로고
    • Strictly proper scoring rules, prediction, and estimation
    • Gneiting T, Raftery AE. Strictly proper scoring rules, prediction, and estimation. J Am Stat Assoc 2007; 102: 359-378.
    • (2007) J Am Stat Assoc , vol.102 , pp. 359-378
    • Gneiting, T.1    Raftery, A.E.2
  • 24
    • 65549136074 scopus 로고    scopus 로고
    • Sampling uncertainty and confidence intervals for the Brier score and Brier skill score
    • Bradley AA, Schwartz SS, Hashino T. Sampling uncertainty and confidence intervals for the Brier score and Brier skill score. Weather and Forecasting 2008; 23: 992-1006.
    • (2008) Weather and Forecasting , vol.23 , pp. 992-1006
    • Bradley, A.A.1    Schwartz, S.S.2    Hashino, T.3
  • 25
    • 67650478018 scopus 로고    scopus 로고
    • On Graphically Checking Goodness-of-fit of Binary Logistic Regression Models
    • Gillmann G, Minder CE. On Graphically Checking Goodness-of-fit of Binary Logistic Regression Models. Methods Inf Med 2009; 48: 306-310.
    • (2009) Methods Inf Med , vol.48 , pp. 306-310
    • Gillmann, G.1    Minder, C.E.2
  • 26
    • 0020552493 scopus 로고
    • The assessment of laboratory tests in the diagnosis of acute appendicitis
    • Marchand A, Van Lente F, Galen RS. The assessment of laboratory tests in the diagnosis of acute appendicitis. Am J Clin Pathol 1983; 80: 369-374.
    • (1983) Am J Clin Pathol , vol.80 , pp. 369-374
    • Marchand, A.1    van Lente, F.2    Galen, R.S.3
  • 28
    • 0031847941 scopus 로고    scopus 로고
    • Expert panel assessment of appropriateness of abdominal aortic aneurysm surgery: Global judgement versus probability estimation
    • Silverstein MD, Ballard DJ. Expert panel assessment of appropriateness of abdominal aortic aneurysm surgery: global judgement versus probability estimation. J Health Serv Res Policy 1998; 3: 134-140.
    • (1998) J Health Serv Res Policy , vol.3 , pp. 134-140
    • Silverstein, M.D.1    Ballard, D.J.2
  • 29
    • 33747603683 scopus 로고    scopus 로고
    • Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: Initial experience
    • Burnside ES, Rubin DL, Fine JP, Shachter RD, Sisney GA, Leung WK. Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience. Radiology 2006; 240: 666-673.
    • (2006) Radiology , vol.240 , pp. 666-673
    • Burnside, E.S.1    Rubin, D.L.2    Fine, J.P.3    Shachter, R.D.4    Sisney, G.A.5    Leung, W.K.6
  • 32
    • 80052272794 scopus 로고    scopus 로고
    • Developmental Validation of the IrisPlex System: Determination of Blue and Brown Iris Colour For Forensic Intelligence
    • Walsh S, Lindenbergh A, Zuniga SB, Sijen T, de Knijff P, Kayser M, et al. Developmental validation of the IrisPlex system: Determination of blue and brown iris colour for forensic intelligence. Forensic Sci Int Genet 2010.
    • (2010) Forensic Sci Int Genet
    • Walsh, S.1    Lindenbergh, A.2    Zuniga, S.B.3    Sijen, T.4    de Knijff, P.5    Kayser, M.6
  • 33
    • 77952567231 scopus 로고    scopus 로고
    • Robust Model-Free Multiclass Probability Estimation
    • Wu Y, Zhang HH, Liu Y. Robust Model-Free Multiclass Probability Estimation. J Am Stat Assoc 2010; 105: 424-436.
    • (2010) J Am Stat Assoc , vol.105 , pp. 424-436
    • Wu, Y.1    Zhang, H.H.2    Liu, Y.3
  • 34
    • 0001595997 scopus 로고
    • Neural network classifiers estimate Bayesian a posteriori probabilities
    • Richard MD, Lippmann RP. Neural network classifiers estimate Bayesian a posteriori probabilities. Neural Comput 1991; 3: 461-483.
    • (1991) Neural Comput , vol.3 , pp. 461-483
    • Richard, M.D.1    Lippmann, R.P.2
  • 35
    • 78649719165 scopus 로고    scopus 로고
    • Non-crossing large-margin probability estimation and its application to robust SVM via preconditioning
    • Wu Y, Liu Y. Non-crossing large-margin probability estimation and its application to robust SVM via preconditioning. Stat Methodol 2011; 8: 56-67.
    • (2011) Stat Methodol , vol.8 , pp. 56-67
    • Wu, Y.1    Liu, Y.2
  • 36
    • 33745174860 scopus 로고    scopus 로고
    • Quantile regression forests
    • Meinshausen N. Quantile regression forests. J Mach Learn Res 2006; 7: 983-999.
    • (2006) J Mach Learn Res , vol.7 , pp. 983-999
    • Meinshausen, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.