The integration of supervised classification and association rules for building classification
models is not new. One major advantage is that models are human readable and can be …

Classification and association rule discovery are important data mining tasks. Using
association rule discovery to construct classification systems, also known as associative …

Associative classification is a promising technique to build accurate classifiers. However, in
large or correlated datasets, association rule mining may yield huge rule sets. Hence …

Association rule discovery and classification are common data mining tasks. Integrating
association rule and classification also known as associative classification is a promising …

Associative classification is a promising technique for the generation of highly precise
classifiers. Previous works propose several clever techniques to prune the huge set of …

Associative classification is a well-known technique for structured data classification. Most
previous works on associative classification use support based pruning for rule extraction …

Given a class model built from a dataset including labeled data, classification assigns a new
data object to the appropriate class. In associative classification the class model (ie, the …

Associative classification is a machine learning approach that aims to build accurate,
effective and compact classification models (classifiers) by combining paradigms from …

There are numerous different classification methods; among the many we can cite
associative classifiers. This newly suggested model uses association rule mining to …

Associative classification is a predictive modeling technique that constructs a classifier
based on class association rules (also known as predictive association rules; PARs). PARs …