APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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If a neural network is overfitting, which of the following would not help
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Introducing dropout
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Reducing the number of layers in the model
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Increasing the capacity of the neural network
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Increasing the size of the training data
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None of the above
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Explanation:
Detailed explanation-1: -Regularization methods are so widely used to reduce overfitting that the term “regularization” may be used for any method that improves the generalization error of a neural network model.
Detailed explanation-2: -Which of the following methods DOES NOT prevent a model from overfitting to the training set? Early stopping is a regularization technique, and can help reduce overfitting. Dropout is a regularization technique, and can help reduce overfitting. Data augmentation can help reduce overfitting by creating a larger dataset.
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