References

Boyd, S., and L. Vandenberghe. 2009. Convex Optimization. 7th ed. Cambridge: Cambridge University Press.

Faraway, J. J. 2009. Linear Models with r. Edited by F. Dominici, J. J. Faraway, M. Tanner, and J. Zidek. London: CRC press.

Hurwitz, J., and D. Kirsch. 2018. Machine Learning for Dummies. New Jersey: John Wiley & Sons.

James, G., D. Witten, T. Hastie, and R. Tibshirani. 2013. An Introduction to Statistical Learning. Edited by G. Casella, Fienberg S, and I. Olkin. New York: Springer.

Krzanowski, W. J. 2000. Principles of Multivariate Analysis: A User’s Perspective. Oxford: Oxford University Press.

Mardia, K. V., J. T. Kent, and J. M. Bibby. 1979. Multivariate Analysis. London: Academic Press.

Mitchell, T. 1997. Machine Learning. McGraw Hill.

Murphy, Kevin P. 2012. Machine Learning : A Probabilistic Perspective. Cambridge: MIT Press.

———. 2022. Probabilistic Machine Learning: An Introduction. Cambridge: MIT Press.

Pearson, Karl. 1901. “On Lines and Planes of Closest Fit to Systems of Points in Space.” Philosophical Magazine, Series 6 11 (2): 559–72.

Weiss, N. A. 2012. Introductory Statistics. Boston: Addison-Wesley Pearson Inc.