The HPSPLIT Procedure

Agresti, A. and Coull, B. A. (1998), “Approximate Is Better Than 'Exact' for Interval Estimation of Binomial Proportions,” American Statistician, 52, 119–126.

Blyth, C. R. and Still, H. A. (1983), “Binomial Confidence Intervals,” Journal of the American Statistical Association, 78, 108–116.

Breiman, L., Friedman, J., Olshen, R. A., and Stone, C. J. (1984), Classification and Regression Trees, Belmont, CA: Wadsworth.

Friedman, J. H. (1977), “A Recursive Partitioning Decision Rule for Nonparametric Classification,” IEEE Transactions on Computers, 26, 404–408.

Hastie, T. J., Tibshirani, R. J., and Friedman, J. H. (2001), The Elements of Statistical Learning, New York: Springer-Verlag.

Kass, G. V. (1980), “An Exploratory Technique for Investigating Large Quantities of Categorical Data,” Applied Statistics, 29, 119–127.

Quinlan, R. J. (1993), C4.5: Programs for Machine Learning, San Francisco: Morgan Kaufmann.

Rokach, L. and Maimon, O. (2008), Data Mining with Decision Trees: Theory and Applications, volume 69 of Series in Machine Perception and Artificial Intelligence, London: World Scientific.

Soman, K. P., Diwakar, S., and Ajay, V. (2010), Insight into Data Mining: Theory and Practice, New Delhi: PHI Learning.

Utgoff, P. E. and Clouse, J. A. (1996), A Kolmogorov-Smirnov Metric for Decision Tree Induction, Technical Report 96-3, University of Massachusetts, Amherst.

Wilson, E. B. (1927), “Probable Inference, the Law of Succession, and Statistical Inference,” Journal of the American Statistical Association, 22, 209–212.