Referencias

Angelopoulos, Anastasios N., and Stephen Bates. 2021. “A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification.” http://arxiv.org/abs/2107.07511.

Bishop, Christopher M. 2006. Pattern Recognition and Machine Learning (Information Science and Statistics). Secaucus, NJ, USA: Springer-Verlag New York, Inc.

Chambers, J. M., W. S. Cleveland, B. Kleiner, and P. A. Tukey. 1983. Graphical Methods for Data Analysis. Chapman & Hall Statistics Series. Wadsworth International Group. https://books.google.com.mx/books?id=I-tQAAAAMAAJ.

Chen, Tianqi, and Carlos Guestrin. 2016. “XGBoost: A Scalable Tree Boosting System.” In, 785–94. https://doi.org/10.1145/2939672.2939785.

Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. MIT Press.

Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. 2017. The Elements of Statistical Learning. Springer Series in Statistics. Springer New York Inc. http://web.stanford.edu/~hastie/ElemStatLearn/.

James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2014. An Introduction to Statistical Learning: With Applications in r. Springer Publishing Company, Incorporated. http://www-bcf.usc.edu/~gareth/ISL/.

Kuhn, M., and K. Johnson. 2013. Applied Predictive Modeling. SpringerLink : Bücher. Springer New York. https://books.google.com.mx/books?id=xYRDAAAAQBAJ.

Shao, Jun. 1993. “Linear Model Selection by Cross-Validation.” Journal of the American Statistical Association 88 (422): 486–94. https://doi.org/10.1080/01621459.1993.10476299.

Srivastava, Nitish, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014. “Dropout: A Simple Way to Prevent Neural Networks from Overfitting.” J. Mach. Learn. Res. 15 (1): 1929–58. http://dl.acm.org/citation.cfm?id=2627435.2670313.