Given a population whose members can be potentially separated into a number of different sets or classes, a classification rule is a procedure in which the elements of the population set are each assigned to one of the classes. A perfect test is such that every element in the population is assigned to the class it really belongs. An imperfect test is such that some errors appear, and then statistical analysis must be applied to analyse the classification.
A special kind of classification rule are binary classifications.
Read more about Classification Rule: Testing Classification Rules, Binary and Multiclass Classification, Table of Confusion, Measuring A Classifier With Sensitivity and Specificity
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