Ch. 20 – Neural Networks. Supplemental slides for CSE 327 Prof. Jeff Heflin. A Neuron. Perceptron Learning. function PERCEPTRON-LEARNING( examples,network) returns a perceptron hypothesis
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Supplemental slides for CSE 327
Prof. Jeff Heflin
function PERCEPTRON-LEARNING(examples,network)returns a perceptron hypothesis
inputs:examples, a set of examples with input x and output y network, a perceptron with weights Wj and activation function g
repeat for each einexamples doErr y[e] – g(in)Wj Wj + Err g’(in) xj[e]until some stopping criteria is satisfiedreturn NEURAL-NET-HYPOTHESIS(network)
From Figure 20.21, p. 742