引用#
[1] Scikit-learn: Machine Learning in Python, Pedregosa et al., JMLR 12, pp. 2825-2830, 2011.
[2] https://en.wikipedia.org/wiki/Ensemble_learning
[3] https://en.wikipedia.org/wiki/Random_forest
[4] https://www.kaggle.com/c/titanic/data
[5] https://en.wikipedia.org/wiki/AdaBoost
[6] Hastie, Trevor; Rosset, Saharon; Zhu, Ji; Zou, Hui (2009). “Multi-class AdaBoost”. Statistics and Its Interface. 2 (3): 349–360.
[7] Friedman J, Hastie T, Tibshirani R. Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors)[J]. The annals of statistics, 2000, 28(2): 337-407.
[8] https://www.cs.toronto.edu/~mbrubake/teaching/C11/Handouts/AdaBoost.pdf
[9] https://www.cs.cmu.edu/~epxing/Class/10701-08s/recitation/boosting.pdf
[10] https://scikit-learn.org/stable/modules/ensemble.html#adaboost
[11] Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning, Second Edition, Springer Series in Statistics, Jan 13, 2017.
[12] Friedman, J.H. (2001) Greedy Function Approximation: A Gradient Boosting Machine. Annals of Statistics, 29, 1189-1232.
[13] A Gentle Introduction to Gradient Boosting https://www.ccs.neu.edu/home/vip/teach/MLcourse/4_boosting/slides/gradient_boosting.pdf