Hands-On Genetic Algorithms with Python

Genetic algorithms solution

To identify the best set of features to be used for our regression test using a genetic algorithm, we've created the Python program 01-solve-friedman.py, which is located at https://github.com/PacktPublishing/Hands-On-Genetic-Algorithms-with-Python/blob/master/Chapter07/01-solve-friedman.py.

As a reminder, the chromosome representation that's being used here is a list of integers with the values of 0 or 1, denoting whether a feature should be used or dropped. This makes our problem, from the point of view of the genetic algorithm, similar to the OneMax problem or the knapsack 0-1 problem we solved previously. The difference is in the fitness function returning the regression model's MSE, which is calculated within ...