Chapter 8
Support Vector Machines
Back in Chapter 3 we looked at the Perceptron, a set of McCulloch and Pitts neurons arranged in a single layer. We identified a method by which we could modify the weights so that the network learned, and then saw that the Perceptron was rather limited in that it could only identify straight line classifiers, that is, it could only separate out groups of data if it was possible to draw a straight line (hyperplane in higher dimensions) between them. This meant that it could not learn to distinguish between the two truth classes of the 2D XOR function. However, in Section 3.4.3, we saw that it was possible to modify the problem so that the Perceptron could solve the problem, by changing the data so that it used ...
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