Similar ruleswould also be present for the other credit-worthiness levels (average
and bad).
The process of building a classifier starts froma sample of data, called a training
set. For each tuple in the training set, the class to which the tuple belongs is
already known. For instance, the training set for a credit-card application may
be the existing customers, with their credit-worthiness determined from their
payment history. The actual data, or population, may consist of all people, including
those who are not existing customers. There are several ways of building
a classifier, as we shall see.