Preference Inconsistence-Based Entropy

Preference analysis is a class of important issues in ordinal decision making. As available information is usually obtained from different evaluation criteria or experts, the derived preference decisions may be inconsistent and uncertain. Shannon entropy is a suitable measurement of uncertainty. This work proposes the concepts of preference inconsistence set and preference inconsistence degree. Then preference inconsistence entropy is introduced by combining preference inconsistence degree and Shannon entropy. A number of properties and theorems as well as two applications are discussed. Feature selection is used for attribute reduction and sample condensation aims to obtain a consistent preference system. Forward feature selection algorithm, backward feature selection algorithm and sample condensation algorithm are developed. The experimental results show that the proposed model represents an effective solution for preference analysis.