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  1. A line or a hyperplane that separates the classes is called a decision boundary. The goal of logistic regression, as with any classifier, is to figure out some way to split the data to allow for an accurate prediction of a given observation’s class using the information present in the features. (For instance, if we were examining the Iris flower dataset, our classifier would figure out some method to split the data based on the following: sepal length, sepal width, petal length, petal width.) In the case of a generic two-dimensional example, the split might look something like this.

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