What are the general limitations of the backpropagation rule?Question 24Answera.Slow convergenceb.Local minima problemc.Alld.scaling
Question
What are the general limitations of the backpropagation rule?Question 24Answera.Slow convergenceb.Local minima problemc.Alld.scaling
Solution
The backpropagation rule, which is widely used in training neural networks, has several limitations:
a. Slow convergence: The backpropagation rule often requires a large number of iterations to converge to the optimal solution. This is because it uses gradient descent to minimize the error function, which can be
Similar Questions
Choose the general limitations of the backpropagation rule among the following.
How can the learning process be stopped in the backpropagation rule?Question 2Answera.There is convergence involved.b. No heuristic criteria exist.c.Noned. Based on the average gradient value
Backpropagation
What is the goal of the backpropagation algorithm in each iteration?Question 4Answera.To minimize the error between the predicted output and the actual outputb.To maximize the error between the predicted output and the actual output in each iterationc.To maximize the error between the predicted output and the actual outputd.To minimize the error between the predicted output and the actual output in each iteration
Backpropagation is capable of handling complex learning problems.1 pointTrueFalse
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