ABSTRACT The Rough Set (RS) theory can be considered as a tool to reduce the input
dimensionality and to deal with vagueness and uncertainty in datasets. Over the years, there …

This paper presents a distributed genetic algorithm for the discovery of classification rules.
Population is contained in the form of interconnected demes. The local selection and …

Knowledge representation and pattern retrieval are the basis of knowledge discovery and
reasoning. Different from many knowledge representation models such as production rules …

The voluminous amount of data stored in databases contains hidden knowledge which
could be valuable to improve decision making process of any organization. As it is not …

Classification is an important data mining task which facilitates list of decision rules that
helps us to predict class of an unseen instance. Various traditional techniques like Decision …

ABSTRACT A majority of contribution in the domain of rule mining overemphasize on
maximizing the predictive accuracy of the discovered patterns. The user-oriented criteria …

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 …

Data mining algorithms produce information of a statistical nature that contains accurate and
reliable knowledge. However, in many cases these algorithms do not discover hidden facts …

The voluminous amount of data stored in databases contains hidden knowledge which
could be valuable to improve decision making process of any organization. As it is not …

Fuzzy rule-based systems (FRBSs) are proficient in dealing with cognitive uncertainties like
vagueness and ambiguity imperative to real-world decision-making situations. Fuzzy …