Association rule discovery is an ever increasing area of interest in data mining. Finding rules
for attributes with numerical values is still a challenging point in the process of association …

Query optimization is a stimulating task of any database system. A number of heuristics have
been applied in recent times, which proposed new algorithms for substantially improving the …

Nature inspired algorithms have become popular for discovering classification rules due to
their ability to effectively handle large and complex search spaces. However, nature inspired …

Knowledge extraction from medical datasets is a challenging task. Medical datasets are
known for their complexity in terms of noise, missing values and imbalanced class …

In this paper, we propose a reduction operator addressing discrete optimization problems,
more precisely, for optimization problems with binary represented decisions. This operator …

This paper presents bottom-up Pittsburgh approach for discovery of classification rules.
Population initialization makes use of entropy as the attribute significance measure and …

Résumé Dans l'exploration de données, de nombreuses techniques sont utilisées pour
extraire des informations utiles. L'une de ces techniques est la classification, la classification …

Goal of classification technique is to predict the class which an instance of dataset belongs
to. Discovered knowledge is then presented in the form of high level, easy to understand …

Genetic Algorithm (GA) is a robust and popular stochastic optimization algorithm for large
and complex search spaces. The major disadvantages of Genetic Algorithms are premature …

Genetic algorithms (GAs) for discovery of classification rules have gained importance due to
their capability of finding global optimal solutions. However, building a rule-based …