What is the bias update rule in backpropagation?Question 13Answera.B(i) = B(i) - alpha * delta(i)b.B(i) = B(i) / alpha * delta(i)c.B(i) = B(i) + alpha * delta(i)d.B(i) = B(i) * alpha * delta(i)
Question
What is the bias update rule in backpropagation?Question 13Answera.B(i) = B(i) - alpha * delta(i)b.B(i) = B(i) / alpha * delta(i)c.B(i) = B(i) + alpha * delta(i)d.B(i) = B(i) * alpha * delta(i)
Solution
The bias update rule in backpropagation is represented by the formula B(i) = B(i) - alpha * delta(i). So, the correct answer is a. B(i) = B(i) - alpha * delta(i).
Here's a step-by-step explanation:
- B(i) represents the current bias of the neuron.
- Delta(i) is the error term for the neuron. It represents how much the output of the neuron is off from the expected output.
- Alpha is the learning rate. It determines how much we adjust the bias in response to the error. A higher learning rate means we adjust the bias more drastically.
- The expression "B(i) - alpha * delta(i)" means we adjust the bias by subtracting a fraction (determined by the learning rate) of the error term from the current bias. This is done to reduce the error in the output of the neuron.
- The updated bias B(i) is then used in the next round of forward and backward propagation.
Similar Questions
What is the bias update rule in the backpropagation algorithm?Question 18Answera.The mathematical formula that is used to update the biases based on the gradient descentb.The process of adjusting the weights and biases in the forward directionc.The process of minimizing the error between the predicted output and the actual outputd.The process of adjusting the weights and biases in the backward direction
What is the weight update rule in backpropagation?Select one:a.W(i, j) = W(i, j) - alpha * delta(i) * output(j)b.W(i, j) = W(i, j) + alpha * delta(i) * output(j)c.W(i, j) = W(i, j) / alpha * delta(i) * output(j)d.W(i, j) = W(i, j) * alpha * delta(i) * output(j)
Question textWhat are the biases in the backpropagation algorithm?Select one:a.The values that are adjusted in the forward passb.The values that are used to determine the output of the neural networkc.The values that are used to determine the activation function of the neural networkd.The values that are adjusted in the backward pass
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
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
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