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Suppose that a training set contains only a single ex, repeated 100 times. In 80 of the 100 cases, the single output value is 1, in other 20 it is 0. What will a back-propagation network predict for this ex, assuming that it has been trained and reaches a global optimum? (Hint: to find the global optimum, differentiate the error function and set to zero.) 

Computer Engineering, Engineering

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