• 1
    Ayers, I. (2007) Super Crunchers: Why Thinking By Numbers Is The New Way To Be Smart. New York: Bantam.
  • 2
    Harrell, F. (2001) Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York: Springer.
  • 3
    Kuhn, M. and Johnson, K. (2013) Applied Predictive Modeling. New York: Springer.
  • 4
    Breiman, L. (1996) Heuristics of instability and stabilization in model selection. Annals of Statistics, 24(6), 23502383.
  • 5
    Snarey, M., Terrett, N., Willett, P. and Wilton, D. (1997) Comparison of algorithms for dissimilarity-based compound selection. Journal of Molecular Graphics and Modelling, 15(6), 372385.
  • 6
    Ambroise, C. and McLachlan, G. (2002) Selection bias in gene extraction on the basis of microarray gene-expression data. Proceedings of the National Academy of Sciences, 99(10), 65626566.
  • 7
    Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B, 58(1), 267288.
  • 8
    Zhu, H. and Hastie, T. (2005) Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society Series B, 67(2), 301320.
  • 9
    Guyon, I., Weston, J., Barnhill, S. and Vapnik, V. (2002) Gene selection for cancer classification using support vector machines. Machine Learning, 46(1), 389422.