Abstract
A large number of our day-to-day experiences and activities are governed by linear phenomena. The distance traveled by a car at a certain speed is linearly related to the duration of the trip. When an object is thrown, its acceleration is a linear function of the amount of force exerted to throw the object. The sales tax owed on a purchased item changes linearly with the item’s original price. The recommended dosages for many medications are linear functions of the patient’s weight. And, the list goes on. Linear regression is the machine learning task of uncovering the hidden linear relationship between the input and output data. In this chapter, we study linear regression from the ground up, laying the foundation for discussion of more complex nonlinear models in the chapters to come.
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References
Lantz B. Machine learning with R. Birmingham: Packt Publishing; 2013
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Borhani, R., Borhani, S., Katsaggelos, A.K. (2022). Linear Regression. In: Fundamentals of Machine Learning and Deep Learning in Medicine. Springer, Cham. https://doi.org/10.1007/978-3-031-19502-0_4
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DOI: https://doi.org/10.1007/978-3-031-19502-0_4
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