Chapter 9. From the Perceptron to Support Vector Machines

In the previous chapter we discussed the perceptron. As a binary classifier, the perceptron cannot be used to effectively classify linearly inseparable feature representations. We encountered a similar problem to this in our discussion of multiple linear regression in Chapter 2, Linear Regression; we examined a dataset in which the response variable was not linearly related to the explanatory variables. To improve the accuracy of the model, we introduced a special case of multiple linear regression called polynomial regression. We created synthetic combinations of features, and were able to model a linear relationship between the response variable and the features in the higher-dimensional ...

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