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The Delta Rule updates the weights of the network to maximize the error between the desired output and the actual output.
The Delta Rule updates the weights of the network to maximize the error between the desired output and the actual output.
False
The Delta Rule calculates the gradient of the error with respect to each weight for weight adjustment.
The Delta Rule calculates the gradient of the error with respect to each weight for weight adjustment.
True
The Delta Rule adjusts the weights based on the positive gradient multiplied by a learning rate.
The Delta Rule adjusts the weights based on the positive gradient multiplied by a learning rate.
False
The Delta Rule is specifically designed for unsupervised learning tasks.
The Delta Rule is specifically designed for unsupervised learning tasks.
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Adapting the Delta Rule for unsupervised learning may involve modifying the error calculation or using additional techniques.
Adapting the Delta Rule for unsupervised learning may involve modifying the error calculation or using additional techniques.
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