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Theory and Methods

On Asymptotic Distributions and Confidence Intervals for LIFT Measures in Data Mining

Pages 1717-1725 | Received 01 Jul 2013, Published online: 15 Jan 2016

REFERENCES

  • Hall, P.G., Hyndman, R.J., Fan, Y. (2004), Nonparametric Confidence Intervals for Receiver Operating Characteristic Curves, Biometrika, 91, 743–750.
  • Horváth, L., Horváth, Z., Zhou, W. (2008), Confidence Bands for ROC Curves,” Journal of Statistical Planning and Inference, 138, 1894–1904.
  • Hsieh, F., Turnbull, B.W. (1996), Nonparametric and Semiparametric Estimation of the Receiver Operating Characteristic Curve, Annals of Statistics, 24, 25–40.
  • Ibragimov, R., Müller, U.K. (2010), t-Statistic Based Correlation and Heterogeneity Robust Inference, Journal of Business and Economic Statistics, 28, 453–468.
  • Jiang, W., Zhao, Y. (2014), Some Technical Details on Confidence Intervals for LIFT Measures in Data Mining, Technical Report 14–02, Department of Statistics, Northwestern University.
  • Lalley, S.P. (2011), Gaussian Processes; Kolmogorov–Chenstov Theorem, available athttp://galton.uchicago.edu/∼lalley/Courses/385/Gauss-ianProcesses.pdf
  • Ma, G., Hall, W.J. (1993), Confidence Bands for Receiver Operating Characteristic Curves, Medical Decision Making, 13, 191–197.
  • Macskassy, S., Provost, F., Rosset, S. (2005a), Pointwise ROC Confidence Bounds: An Empirical Evaluation, Proceedings of the Workshop on ROC Analysis in Machine Learning (ROCML-2005) at ICML-2005.
  • Macskassy, S., Provost, F., Rosset, S. (2005b), “ROC Confidence Bands: An Empirical Evaluation,” in Proceedings of the 22nd International Conference on Machine Learning (ICML). Bonn, Germany.
  • Moore, D.S. (2010), The Basic Practice of Statistics ( 5th ed.), New York: W. H. Freeman.
  • Rosset, S., Neumann, E., Eick, U., Vatnik, N., and Idan, I. (2001), Evaluation of Prediction Models for Marketing Campaigns, KDD-01. pp. 456–461, ACM Press. Available at http://www.tau.ac.il/∼saharon/papers/Evaluation%20of%20Prediction%20Models.pdf.
  • SAS Institute Inc. (2003), Data Mining Using SASR Enterprise MinerTM: A Case Study Approach ( 2nd ed.), Cary, NC: SAS Institute Inc. Available at http://support.sas.com/documentation/onlinedoc/miner/casestudy_59123.pdf.
  • Stine, R.A., Foster, D.P., and Waterman, R.P. (1998), Business Analysis Using Regression: A Casebook, New York: Springer.
  • Su, H., Qin, Y., Liang, H. (2009), Empirical Likelihood-Based Confidence Interval of ROC Curves, Statistics in Biopharmaceutical Research, 1, 407–414.
  • van der Vaart, A.W., and Wellner, J. (1996), Weak Convergence and Empirical Processes, New York: Springer.
  • Zhao, Y. (2014), On Asymptotic Distributions and Confidence Intervals for LIFT Measures in Data Mining, PhD Dissertation, Northwestern University.

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