Most classification methods are based on building a model in the training phase, and then using this model for specific test instances, during the actual classification phase. Thus, the classification process is usually a two-phase approach that is cleanly separated between processing training and test instances. As discussed in the introduction chapter of this book, these two phases are as follows:
Training Phase: In this phase, a model is constructed from the training instances.
Testing Phase: In this phase, the model is used to assign a label to an unlabeled test instance.