2CLASSIFICATION MODELS
The last chapter briefly introduced classification applications, in which we predict dummy or categorical variables. These differ from the numeric applications we’ve analyzed, such as predicting the number of bike riders, which is a numeric entity. For instance, in a marketing application, we might wish to predict whether a customer will purchase a certain product. In that case, we’d represent the “Y” outcome with a dummy variable, using 1 for buying the item and 0 for not buying it. There are two classes here: Buy and Not Buy.
We discussed an example of categorical Y in the “Some Terminology” box in Section 1.1. In that ...
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