7.2 CLASSIFICATION EVALUATION MEASURES
We will develop classification evaluation measures for the case where we have a binary target variable. In order to apply the measures we will learn in this chapter, we will need to denote (arbitrarily, if desired) one of the two target outcomes as positive and one as negative. For example, suppose we are trying to predict income, a binary variable with values high income and low income. We could denote high income as positive and low income as negative.1
Now, the classification model evaluation measures we will learn in this chapter are functions of the entries in the contingency table2 generated by the classification model, the general form of which is shown in Table 7.1. Note that, by convention, the actual values are represented by the rows, while the predicted values are represented by the columns. The upper‐left cell in Table 7.1 represents the number of records where the model predicted a negative response and the actual response value...