Linear-Genetic-Programming-Project-on-the-regression-problem Implementation a Linear Genetic Programming algorithm on the Mexican Hat regression problem.

a) We Choose a representative single run, and use two figures to show its evolutionary progression. Figure 1 shows both the fitness of the best individual and the average fitness of the population, in relation to the number of generations. Figure 2 shows the largest program length and the average program length, in relation to the number of generations.

b) We run our algorithm 10 times and use a table to show the fitness of the 10 best-of-run models and their mean and standard deviation.

c) We Show the one best Linear Genetic Programming model we ever find. We also remove the structural and semantic (approximately) introns.