| [1] | Mjolsness E, DeCoste D (2001) Machine learning for science: State of the art and future prospects. Science 93: 2051–2055.
|
| [2] | Bishop CM (2006) Pattern Recognition and Machine Learning (Information Science and Statistics). Springer.
|
| [3] | Hand D (2001) Measuring diagnostic accuracy of statistical prediction rules. Statistica Neerlandica 55: 3–16.
|
| [4] | Breiman L (2001) Random forests. Machine Learning 45: 5–32.
|
| [5] | Claeskens G, Hjort NL (2008) Model selection and model averaging.Cambridge University Press.
|
| [6] | Simon R, Radmacher MD, Dobbin K, McShane LM (2003) Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst 95: 14–8.
|
| [7] | Steyerberg EW (2008) Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (Statistics for Biology and Health). Springer. 1 edition.
|
| [8] | Savage LJ (1971) Elicitation of personal probabilities and expectations. JASA 66: 783–801.
|
| [9] | Hilden J, Habbema JDF, Bjerregaard B (1978) The measurement of performance in probabilistic diagnosis — III. Methods based on continuous functions of the diagnostic probabilities. Methods of Information in Medicine 17: 238–246.
|
| [10] | Gneiting T, Raftery AE (2007) Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association 102: 359–378.
|
| [11] | Efron B (1983) Estimating the error rate of a prediction rule: Improvement on cross-validation. Journal of the American Statistical Association 78: 316–331.
|
| [12] | Davison AC, Hinkley DV (1997) Bootstrap methods and their application, volume 1 of Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge: Cambridge University Press.
|
| [13] | Fu WJ, Carroll RJ, Wang S (2005) Estimating misclassification error with small samples via bootstrap cross-validation. Bioinformatics 21: 1979–1986.
|
| [14] | Jiang W, Simon R (2007) A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classification. Statistics in Medicine 26: 5320–34.
|
| [15] | Gerds TA, Cai T, Schumacher M (2008) The performance of risk prediction models. Biometrical Journal 50: 457–479.
|
| [16] | Vapnik V (1982) Estimation of dependences based on empirical data. Springer Series in Statistics. New York: Springer-Verlag. Translated from the Russian by Samuel Kotz.
|
| [17] | Tibshirani R (1996) Regression shrinkage and selection via the LASSO. J Roy Statist Soc Ser B 58: 267–288.
|
| [18] | Efroymson MA (1960) Multiple regression analysis. Mathematical methods for digital computers. New York: Wiley. pp. 191–203.
|
| [19] | Becker U, Fahrmeir L (2001) Bump hunting for risk: a new data mining tool and its applications. Comput Statist 16: 373–386.
|
| [20] | Breiman L (2001) Statistical modeling: The two cultures. (With comments and a rejoinder). Statistical Sciences 16: 199–231.
|
| [21] | Raftery AE, Madigan D, Hoeting JA (1997) Bayesian model averaging for linear regression models. J Amer Statist Assoc 92: 179–191.
|
| [22] | Dawid AP (1986) Probability forecasting. Encyclopedia of Statistical Sciences (9 vols. plus Supplement), Wiley:NY:UK. volume 7. Wiley:NY:UK: pp. 210–218.
|
| [23] | Gerds TA, Schumacher M (2006) Consistent estimation of the expected Brier score in general survival models with right-censored event times. Biometrical Journal 48: 1029–1040.
|
| [24] | Matheson J, Winkler (1976) Scoring rules for continuous probability distributions. Management Science 22: 1087–1096.
|
| [25] | S？rensen TIA, Boutin P, Taylor M, Larsen L, Verdich C, et al. (2006) Genetic polymorphisms and weight loss in obesity: a randomised trial of hypo-energetic high- versus low-fat diets. PLoS Clinical Trials 1: e12.
|
| [26] | Pers T, Martin F, Verdich C, Holst C, Johansen J, et al. (2008) Prediction of fat oxidation capacity using 1h-nmr and lc-ms lipid metabolomic data combined with phenotypic data. Chemometrics and Intelligent Laboratory Systems 93: 34–42.
|
| [27] | Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. The Wadsworth Statistics/Probability Series. Belmont, California.
|
| [28] | Efron B, Hastie T, Johnstone I, Tibshirani R (2004) Least angle regression. Ann Statist 32: 407–499.
|
| [29] | R Development Core Team (2008) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL . ISBN 3-900051-07-0.
|
| [30] | Liaw A, Wiener M (2002) Classification and regression by randomforest. R News 2: 18–22.
|
| [31] | Dimitriadou E, Hornik K, Leisch F, Meyer D, et al. (2009) e1071: Misc Functions of the Department of Statistics (e1071), TU Wien. R package version 1.5-19.
|
| [32] | Hastie T, Efron B (2007) lars: Least Angle Regression, LASSO and Forward Stagewise. URL . R package version 0.9-7.
|
| [33] | Zhang X, Lu X, Shi Q, Xu XQ, Leung HCE, et al. (2006) Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data. BMC Bioinformatics 7: 197.
|
| [34] | Ma S, Song X, Huang J (2007) Supervised group Lasso with applications to microarray data analysis. BMC Bioinformatics 8: 60.
|
| [35] | Fusaro VA, Mani DR, Mesirov JP, Carr SA (2009) Prediction of high-responding peptides for targeted protein assays by mass spectrometry. Nat Biotechnol 27: 190–8.
|
| [36] | Gerds TA, Schumacher M (2007) On Efron type measures of prediction error for survival analysis. Biometrics 63: 1283–1287.
|
| [37] | Efron B, Tibshirani R (1997) Improvement on cross-validation: The .632+ bootstrap method. Journal of the American Statistical Association 92: 548–560.
|
| [38] | Binder H, Schumacher M (2008) Adapting prediction error estimates for biased complexity selection in high-dimensional bootstrap samples. Statistical Applications in Genetics and Molecular Biology 7: Article 12.
|
| [39] | Politis DN, Romano JP, Wolf M (1999) Subsampling. Springer Series in Statistics. New York: Springer.
|
