InterviewSolution
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InterviewSolution
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If e(m) denotes error for correction of weight then what is formula for error in perceptron learning model: w(m + 1) = w(m) + n(b(m) – s(m)) a(m), where b(m) is desired output, s(m) is actual output, a(m) is input vector and ‘w’ denotes weight(a) e(m) = n(b(m) – s(m)) a(m)(b) e(m) = n(b(m) – s(m))(c) e(m) = (b(m) – s(m))(d) none of the mentionedThis question was addressed to me by my college director while I was bunking the class.This question is from Pattern Classification in portion Feedforward Neural Networks of Neural Networks |
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Answer» Right answer is (C) E(m) = (b(m) – s(m)) |
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