1. Let D denote the set of training examples, ta denote the true target value of an example d in D, where d is represented by feature vector (x1,X2,...Xn), and oa be the predicted value (i.e. output)....

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Extracted text: 1. Let D denote the set of training examples, ta denote the true target value of an example d in D, where d is represented by feature vector (x1,X2,...Xn), and oa be the predicted value (i.e. output). Define the output function: f(x1,X2,...Xn) = Wotwixi+wiX1+W2X2+w2X2+...+WhXn+WnXn Derive a gradient descent training rule for a single learning unit with the output as defined above.