My idea is simple.
Using pyevolve and a score as the accuracy of the machine learning classifier. I wonder if you can just evolve the extra input data for better classification. That is. I belive you can create features from random or the evolved genome that will help in the classification. In theory it might work. I will see how well it works.
Even using a spline function with a limited number of parameters. The decision boundary for the classifier was too unpredictable.
From the image you can see that the decision areas look pretty neat. But probably wrong. There are lots of information that might be handy to the algorithm. Also I think neat decision areas are somewhat not complex enough. For instance you could define problem areas with another third color and call it problem area. The areas with suspect decision boundary.
Maybe you can run a ?generative model on this one. Here you generate new data that are “photo realistic”. That is. The data is belivable.
If machine learning is going to used for cars then I think it has to mature a lot. I mean they are trying to simulate brain functions with classifiers that could have very strong score for confidense but wrong anyway.
In my opinon machine learning is still in experimental stage. When its matured enough to be boring. Because the many ?security measures. Then self driving cars could be a goal.
I believe we need much more confidence and accuracy type measurements. For example. I would have to have much more points precisely at the decision boundary. So its not only how many samples you have but also how much the samples reveal the boundary and more.
On a further note. If we develop self driven cars. Where is it going to stop. People will loose their jobs and then who will pay for those cars. The sallory goes to the robots. The little tax that comes from them will pay for the roads.
However I think machine learning could be used to reveal what there is to know about the universe. Physics that will give us much better batteries for human driven cars. Fusion energy to help us survive.