V. ASSOCIATIVE CLASSIFICATION
Associative classification is a recent and rewarding technique which integrates association rule mining and
classification to a model for prediction and achieves maximum accuracy. Associative classifiers are especially fit to
applications where maximum accuracy is desired to a model for prediction.
Association rule mining and classification are two main functionalities of data mining. Association rule mining
is used to find associations or correlations among the item sets. It is a unsupervised learning where no class attribute is
involved in finding the association rule. On the other hand, classification is a supervised learning where class attribute is
involved in the construction of the classifier and is used to classify or predict the data unknown sample.
Associative classification involves two stages.