A novel algorithm, CorClass, that integrates association rule mining with classification, is
presented. It first discovers all correlated association rules (adapting a technique by …

Decision trees are among the most effective and interpretable classification algorithms while
ensembles techniques have been proven to alleviate problems regarding over-fitting and …

When using unordered rule sets, conflicts can arise between the rules, ie, two or more rules
cover the same example but predict different classes. This paper gives a survey of methods …

When applying an unordered set of classification rules, the rules may assign more than one
class to a particular example. Previous methods of resolving such conflicts between rules …

Incremental reduced error pruning is a technique that has been extensively used for efficient
induction of ordered rule sets (decision lists). Several criteria have been developed …

In software engineering design anti-patterns are commonly used bad solutions for a
recurring problem in software design. They are frequently equated with specific structures in …

We consider the problem of discovering the optimal pair of substring patterns with bounded
distance α, from a given set S of strings. We study two kinds of pattern classes, one is in form …

The rule conflict is an important issue for associative classification due to a large set of rules.
In this paper, a new approach called Associative Classification with Bayes (AC-Bayes) is …

Associative classification usually generates a large set of rules. Therefore, it is inevitable that
an instance matches several rules which classes are conflicted. In this paper, a new …

Decision lists (or ordered rule sets) have two attractive properties compared to unordered
rule sets: they require a simpler classification procedure and they allow for a more compact …