I believe anyone who has considered applying machine learning tools for identifying trading signals came across the idea of using some kind of optimization algo

I believe anyone who has considered applying machine learning tools for identifying trading signals came across the idea of using some kind of optimization algorithm to find the best parameters. Evolutionary algorithms seem like a fair approach because the parameter space is (for lack of a better word) very sparse and anything but continuous (lots of parameter combinations don't make sense / don't work). Using a genetic algorithm - like for example the differential evolution algorithm by Price, Storn and Lampinen - is really the most naive approach. I assume they must have some pretty clever, human made models in the back - because in a very general model the parameter space would be so vast, they would probably never find good parameters. And even if they did, they would have to run thousands of tests to make sure they are not overfitting the data - making this a very slow optimization. Not saying this will or will not work - I'm just thinking out loud here.