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Binary classification is the task of classifying the elements of a set into two groups on the basis of a classification rule. Typical binary classification problems include:

Binary classification is dichotomization applied to a practical situation. In many practical binary classification problems, the two groups are not symmetric, and rather than overall accuracy, the relative proportion of different types of errors is of interest. For example, in medical testing, detecting a disease when it is not present is considered differently from not detecting a disease when it is present.

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