Suppose that a training set contains only a single example, repeated 100
times. In 80 of the 100 cases, the single output value is 1; in the
other 20, it is 0. What will a back-propagation network predict for this
example, assuming that it has been trained and reaches a global optimum?
(

*Hint:*to find the global optimum, differentiate the error function and set it to zero.)*Hint:* to find the global optimum, differentiate the
error function and set it to zero.)