I have created a neural network in 'nftool' with 10 inputs and 20 outputs using 5283 samples and found that the architecture with 16 hidden layer neurons gives least performance error of 0.012. I have tried using same properties in 'nntool' and expected to get same error. These were the network properties:
Network Type: Feed-forward backprop Input Ranges: Got from Input Adaptation Function: LEARNGDM Number of Layers: 2 Properties : Layer 1 Layer 2 16 Neurons 20 Neurons LOGSIG PURELIN
However, when I train this network I get a performance error of around 0.5. Why is the error much larger?
Best Answer