Abstract
This chapter explains the basics of simple linear regression. Showing different approaches to solve a prediction problem of this type. First, we explain the theory, then, it is solved by the algebraic method of least squares, checking the procedure and results through MATLAB. Finally, a basic example of the field of evolutionary computing is shown, using several evolutionary techniques such as PSO, DE, ABC, CS and the classical method of descending gradient. Which optimize the function to find the best coefficients for an estimated straight line. This is applied to a set of fatal traffic accident data in the U.S. states.
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Islas Toski, M., Avila-Cardenas, K., Gálvez, J. (2020). Linear Regression Techniques for Car Accident Prediction. In: Oliva, D., Hinojosa, S. (eds) Applications of Hybrid Metaheuristic Algorithms for Image Processing. Studies in Computational Intelligence, vol 890. Springer, Cham. https://doi.org/10.1007/978-3-030-40977-7_12
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DOI: https://doi.org/10.1007/978-3-030-40977-7_12
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