CODEWITHSUNDEEP
kerasdeep-learningneural-networktensorflow2.0
Subhash
Subhash

Reputation: 33

How to prioritize few Neural Network inputs?

I have a Neural Network with five inputs for a classification task. Two inputs out of those five are very important and have a direct relationship to the classification task. Therefore, I need to prioritize those two inputs within the network and give less priority to the other three. Is there a way in the neural network to facilitate my requirement?

Upvotes: 0

Views: 428

Answers (1)

Ananda
Ananda

Reputation: 3272

If training works well, the NN should automatically pick up what's most important for your classification. That's the entire point of a NN (or ML in general); so that you don't have to manually tell it what's more important and what's not. After learning, you can verify that the model indeed does learn the correct order of importance between the features.

You can use any model explanation technique for this. ELI5, SHAP or LIME are some examples. All these will tell you if your model did indeed learn that the features that you know are important is actually important to the network.

You probably shouldn't try to manually incorporate such biases into the network (unless you have a very good reason for doing so, like incorporating spatial information of images via CNNs). Trust the learning xD

Upvotes: 2

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