# 15.5 文献笔记¶

1. Breiman, L. (2001). Random forests, Machine Learning 45: 5–32.

2. Ho, T. K. (1995). Random decision forests, in M. Kavavaugh and P. Storms (eds), Proc. Third International Conference on Document Analysis and Recognition, Vol. 1, IEEE Computer Society Press, New York, pp. 278–282.

3. Kleinberg, E. M. (1990). Stochastic discrimination, Annals of Mathematical Artificial Intelligence 1: 207–239.

4. Kleinberg, E. M. (1996). An overtraining-resistant stochastic modeling method for pattern recognition, Annals of Statistics 24: 2319–2349.

5. Amit, Y. and Geman, D. (1997). Shape quantization and recognition with randomized trees, Neural Computation 9: 1545–1588.

6. Breiman, L. (1996a). Bagging predictors, Machine Learning 26: 123–140.

7. Dietterich, T. (2000b). An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization, Machine Learning 40(2): 139–157.

8. Friedman, J. and Hall, P. (2007). On bagging and nonlinear estimation, Journal of Statistical Planning and Inference 137: 669–683.