The ability to understand and explain the outcomes of data analysis methods, with regard to
aiding decision-making, has become a critical requirement for many applications. For …

Abstract Multiple Criteria Decision Analysis (MCDA) is a subfield of Operational Research
that aims to support Decision-Makers (DMs) in the decision-making process through …

Dominance-based rough approximation discovers inconsistencies from ordered criteria and
satisfies the requirement of the dominance principle between single-valued domains of …

Ordinal regression problems are those machine learning problems where the objective is to
classify patterns using a categorical scale which shows a natural order between the labels …

We formulate some questions that may help an analyst to choose a multicriteria decision
aiding method well adapted to the decision context. These questions take into account …

Currently, knowledge discovery in databases is an essential first step when identifying valid,
novel and useful patterns for decision making. There are many real-world scenarios, such as …

The processing scheme of typical incomplete information systems has been widely explored
nowadays, however most of these approaches may change the original data information …

Uncertainty and fuzziness generally exist in real-life data. Approximations are employed to
describe the uncertain information approximately in rough set theory. Certain and uncertain …

This article investigates the Game-theoretic Rough Set (GTRS) model and its capability of
analyzing a major decision problem evident in existing probabilistic rough set models. A …

Feature selection methods with antinoise performance are effective dimensionality reduction
methods for classification tasks with noise. However, there are few studies on robust feature …