What is the error function in the backpropagation algorithm?Question 5Answera.The function that adjusts the weights and biases in the forward passb.The function that calculates the error between the predicted output and the actual outputc.The function that determines the activation function of the neural networkd.The function that adjusts the weights and biases in the backward pass
Question
What is the error function in the backpropagation algorithm?Question 5Answera.The function that adjusts the weights and biases in the forward passb.The function that calculates the error between the predicted output and the actual outputc.The function that determines the activation function of the neural networkd.The function that adjusts the weights and biases in the backward pass
Solution
The error function in the backpropagation algorithm is the function that calculates the error between the predicted output and the actual output.
Here's a step-by-step explanation:
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The backpropagation algorithm is used in a neural network to adjust the weights and biases in response to the error found during training.
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The error function, also known as the loss function or cost function, is a crucial part of this algorithm.
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After the forward pass (where inputs are fed into the network and an output is produced), the predicted output is compared to the actual output.
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This comparison results in an error value, which is calculated by the error function.
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The goal of the backpropagation algorithm is to minimize this error.
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In the backward pass, the error is propagated back through the network. This means that the weights and biases are adjusted in reverse order, starting from the output layer and moving towards the input layer.
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These adjustments are made in a way that would decrease the error if the same inputs were to be fed into the network again.
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The specific adjustments are determined by the derivative of the error function, which is why the choice of error function is important.
So, the correct answer is b. The function that calculates the error between the predicted output and the actual output.
Similar Questions
What is the forward pass in the backpropagation algorithm?Question 12Answera.The process of adjusting the weights and biases in the backward directionb.The process of adjusting the weights and biases in the forward directionc.The process of calculating the error between the predicted output and the actual outputd.The process of predicting the output of the neural network based on the input data
What is the process of adjusting the weights and biases based on the error in the output layer called?Select one:a.Backpropagationb.None of the abovec.Forward propagationd.Activation
What is the gradient descent in the backpropagation algorithm?Question 6Answera.The process of minimizing the error between the predicted output and the actual outputb.The process of adjusting the weights and biases in the forward directionc.The process of adjusting the weights and biases in the backward directiond.The process of maximizing the error between the predicted output and the actual output
How does the backpropagation algorithm work?Select one:a.By adjusting the weights and biases of the neural network in the forward passb.By adjusting the activation function of the neural networkc.By adjusting the weights and biases of the neural network in the backward passd.By adjusting the weights and biases of the neural network in both the forward and backward passes
What are the weights in the backpropagation algorithm?Question 10Answera.The values that are used to determine the output of the neural networkb.The values that are adjusted in the backward passc.The values that are used to determine the activation function of the neural networkd.The values that are adjusted in the forward pass
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