Neat disconnected

[chill0chill]

Hi, I am running a NEAT with more than 28 features and comparing it with a deep backprop network. I am running a regression problem.After running multiple configurations(pop size, crossover, mutation rate, connection add rate , etc). I am observing that neat is leaving out important features from the network if initial state is unconnected. If i start with fully connected network , then the accuracy is dropping a lot. Not to mention both the methods are underperforming deep fully connected network. Has anybody else faced this issue or does anybody has a thought on this problem?

[mathiasose]

I did some thinking about this a while back, but I didn't implement it, so take that into consideration:

It might be beneficial to create a fitness function that rewards both objective score and smaller numbers of connections and/or hidden neurons. So if two different networks perform the same at the objective task, the smaller of the two networks would get a higher fitness score than the other. This would create a selection pressure towards smaller networks, which might make the solution space exploration more efficient (assuming the task can in fact be solved by a small network).

In your case you might also want to try starting with partially (randomly) connected initial states, not just fully connected and fully disconnected.

[winatawelly]

Hi, I am running a NEAT with more than 28 features and comparing it with a deep backprop network. I am running a regression problem.After running multiple configurations(pop size, crossover, mutation rate, connection add rate , etc). I am observing that neat is leaving out important features from the network if initial state is unconnected. If i start with fully connected network , then the accuracy is dropping a lot. Not to mention both the methods are underperforming deep fully connected network. Has anybody else faced this issue or does anybody has a thought on this problem?

Do you ever found any solution to this problem ?
i also running regression problem with 22 features and just noticed that most features doesnt even make it to the output node.

[ntraft]

I'm not sure what you mean by "disconnected" and "most features doesn't even make it to the output node", but it sounds like you may be impacted by the issue I filed just now: #255.