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All the following statements about hidden layers in artificial neural networks are true EXCEPT more hidden layers increase required computation exponentially. more hidden layers include many more weights. many top commercial ANNs forgo hidden layers completely. hidden layers are not direct inputs or outputs.

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Answer:

many top commercial ANNs forgo hidden layers completely

User Garth
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Answer:

The answer is many top commercial ANNs forgo hidden layers completely.

Step-by-step explanation:

Hidden layers are artificial neural networks which her directly hidden in between input layers and output layers. It increase the required computation exponentially, improves prediction capabilities and they are not visible as a network output. It ensures there it calculates the weighted inputs and net inputs to produce the actual output. The more the number of hidden layers in a neural network, the longer it takes for it to produce the output and it will enable the neural network to solve more complex problems.

User Jim Flanagan
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