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Question textHow does a backpropagation network learn?Select one:a.By adjusting the number of neurons in the network based on the input and output datab.By adjusting the weights and biases of the network based on the input and output datac.By adjusting the activation function of the network based on the input and output datad.By adjusting the architecture of the network based on the input and output data

Question

Question textHow does a backpropagation network learn?Select one:a.By adjusting the number of neurons in the network based on the input and output datab.By adjusting the weights and biases of the network based on the input and output datac.By adjusting the activation function of the network based on the input and output datad.By adjusting the architecture of the network based on the input and output data

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Solution

The backpropagation network learns by adjusting the weights and biases of the network based on the input and output data. So, the correct answer is option b.

Here's a step-by-step explanation:

  1. Initialize the network with random weights and biases.

  2. Feed the network with input data.

  3. Compute the output of the network.

  4. Compare the computed output with the desired output. This will give the error of the network.

  5. Use the backpropagation algorithm to propagate this error back through the network. This means adjusting the weights and biases of the network in such a way that the error is minimized.

  6. Repeat steps 2-5 for many iterations, or until the network's performance is satisfactory. This process is also known as training the network.

  7. After the network is trained, it should be able to make accurate predictions on new, unseen data.

This problem has been solved

Similar Questions

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 is the backpropagation algorithm used for?Question 10Answera.To optimize the activation function of a neural networkb.To find the optimal weights and biases of a neural networkc.To classify data using a neural networkd.All of the above

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 learning rate in backpropagation?Select one:a.The process of adjusting the weights and biases in the forward directionb.The hyperparameter that determines the size of the weight and bias updatesc.The process of adjusting the weights and biases in the backward directiond.The process of minimizing the error between the predicted output and the actual output

How does backpropagation learn in artificial neural network(ANN) work?

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