What is the main advantage of using dropout in neural networks? In Machine Learning🤖?
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Answer: B) To reduce overfitting
Explanation: Dropout is a regularization technique used in neural networks to reduce overfitting by randomly dropping units during training, preventing the network from relying too heavily on specific nodes.
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