What is the cost function used in backpropagation?Question 4Answera.The hinge lossb.The cross-entropy lossc.The mean absolute errord.The mean squared error

The cost function used in backpropagation is b. The cross-entropy loss.

Here's a step-by-step explanation:

1. Backpropagation is a method used in artificial neural networks to calculate the gradient of the loss function with respect to the weights of the network.

2. The loss function is a measure of how well the neural network is performing with respect to its given training sample and the expected output.

3. The cross-entropy loss function is commonly used in classification problems.

4. The cross-entropy loss for a binary or two class prediction problem is a negative logarithm of the predicted probability for the actual class value.

5. The benefit of using cross-entropy loss is that it can provide a lot of information if the prediction is totally wrong, i.e., it predicted 0 (zero probability) when it should have predicted 1, and vice versa.

6. Therefore, in the context of backpropagation, the cross-entropy loss function is used to adjust the weights of the neural network in the direction that minimizes the loss, or the difference between the actual and predicted values.