References

Breiman, Leo et al. 2001. “Statistical Modeling: The Two Cultures (with Comments and a Rejoinder by the Author).” Statistical Science 16 (3): 199–231.
Buckland, Michael, and Fredric Gey. 1994. “The Relationship Between Recall and Precision.” Journal of the American Society for Information Science 45 (1): 12–19.
Chawla, Nitesh V, Kevin W Bowyer, Lawrence O Hall, and W Philip Kegelmeyer. 2002. “SMOTE: Synthetic Minority over-Sampling Technique.” Journal of Artificial Intelligence Research 16: 321–57.
Efron, Bradley, and Trevor Hastie. 2016. Computer Age Statistical Inference. Vol. 5. Cambridge University Press.
Faraway, Julian J. 2016. Linear Models with r. Chapman; Hall/CRC.
Goodfellow, Ian, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. Vol. 1. MIT Press Cambridge.
Harrell, Frank. 2017. “Classification Vs. Prediction.” 2017. https://www.fharrell.com/post/classification/.
Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Vol. 2. Springer Science+ Business Media.
Kuhn, Max, and Kjell Johnson. 2013. Applied Predictive Modeling. Vol. 26. Springer.
———. 2019. Feature Engineering and Selection: A Practical Approach for Predictive Models. Chapman; Hall/CRC.
Kutner, M. H., C. J. Nachtsheim, J. Neter, and W. Li. 2005. Applied Linear Statistical Models. 5th ed. McGraw Hill.
Lipovetsky, Stan. 2020. Taylor & Francis.
Mnih, Volodymyr, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin A. Riedmiller. 2013. “Playing Atari with Deep Reinforcement Learning.” CoRR abs/1312.5602. http://arxiv.org/abs/1312.5602.
Powell, Warren B. 2021. “From Reinforcement Learning to Optimal Control: A Unified Framework for Sequential Decisions.” In Handbook of Reinforcement Learning and Control, 29–74. Springer.
Sutton, Richard S, and Andrew G Barto. 2018. Reinforcement Learning: An Introduction. MIT press.
Szepesvári, Csaba. 2022. Algorithms for Reinforcement Learning. Springer Nature.
Wickham, Hadley. 2014. Advanced r. CRC Press.
Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media, Inc.
Wolpert, David H. 1996. “The Lack of a Priori Distinctions Between Learning Algorithms.” Neural Computation 8 (7): 1341–90.