title: GA trained NN performs worse on Test Set than BP trained NN
body: <p>I trained a Neural Network with a GA and with Backpropagation. The GA finds suitable weights for the training data but performs poorly on the test data. If I train the NN with BackPropagation, it performs much better on the test data even though the training error isn't much smaller than for the GA trained version. Even when I use the weights obtained by the GA as initial weights for Backpropagation, the NN performs worse on the test data than using only Backpropagation for training. Can anyone tell me where I could have made a mistake?</p>