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I feel confused about how to design a Multilayer Perceptron(MLP). I have read a number of papers about how to design a deep CNN structure, like VGG or ResNet. However, for a Multilayer perceptron, a more basic ANN structure, should I follow this trend to make the MLP deeper? Actually, I try some trials on python that stacking more layers in one network, but the result showed it make no sense.

Therefore, I just wanna ask the question above.

can anybody give me some suggestions?

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The optimal neural network architecture depends on your data set.

FYI:

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