How does the Quickprop algorithm handle weight updates that are too large?Question 11Answera.It reduces the weight updatesb.It discards the weight updatesc.It increases the learning rated.It reduces the learning rate
Question
How does the Quickprop algorithm handle weight updates that are too large?Question 11Answera.It reduces the weight updatesb.It discards the weight updatesc.It increases the learning rated.It reduces the learning rate
Solution 1
The Quickprop algorithm handles weight updates that are too large by reducing the weight updates. This is done to prevent the algorithm from overshooting the minimum of the cost function. If the weight updates are too large, the algorithm may not converge to the minimum and may instead oscillate around it. By reducing the weight updates, the Quickprop algorithm ensures that it takes smaller steps towards the minimum, increasing the chances of convergence.
Solution 2
The Quickprop algorithm handles weight updates that are too large by reducing the weight updates. This is done to prevent the algorithm from overshooting the minimum of the cost function. If the weight updates are too large, the algorithm may not converge to the optimal solution. Therefore, by reducing the weight updates, the Quickprop algorithm ensures that it takes smaller steps towards the minimum of the cost function, thereby increasing the chances of finding the optimal solution.
Similar Questions
How does the Quickprop algorithm adjust the learning rate for each weight in the neural network?Select one:a.It adjusts the learning rate based on the previous weight updateb.It uses a fixed learning rate for all weightsc.It uses a variable learning rate for all weightsd.It uses a fixed learning rate for some weights and a variable learning rate for others
How does the Quickprop algorithm improve upon traditional gradient descent algorithms?Question 7Answera.It uses a larger learning rateb.It uses a variable learning ratec.It uses a smaller learning rated.It uses a fixed learning rate
What is the Quickprop algorithm used for?Select one:a.Data analysisb.Machine learningc.Neural network trainingd.Data visualization
What is the main advantage of the Quickprop algorithm over the backpropagation algorithm?Select one:a.It is more accurateb.It is less sensitive to initializationc.It is more efficientd.It is faster to converge
What is the main advantage of the Quickprop algorithm over the backpropagation algorithm?Question 9Answera.It is more efficientb.It is faster to convergec.It is less sensitive to initializationd.It is more accurate
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