In a neural network, inputs that are important in predicting the output have smaller weights, whereas the less important inputs have larger weights.

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In a neural network, inputs that are more important for predicting the output typically have larger weights, as these weights amplify the influence of the input on the network's decision. Less important inputs tend to have smaller weights, reducing their impact on the output.

In a Neural Network, Inputs That Are Important in Predicting