A three-way decision method based on Gaussian kernel in a hybrid information system with images: An application in medical diagnosis

Abstract

An information system as a database that expresses relationships between objects and attributes is an important mathematical model in the field of artificial intelligence. A hybrid information system with images is an information system which exists many kinds of data (e.g., boolean, categorical, real-valued, set-valued, interval-valued, images and missing data). This paper proposes a three-way decision method based on Gaussian kernel in a hybrid information system with images and gives an application in medical diagnosis. The distance between two objects based on the conditional attribute set in a hybrid information system with images is first given. Then, the fuzzy Tcos-equivalence relation, induced by a hybrid information system with images by using Gaussian kernel, is obtained. Next, the decision-theoretic rough set model for a hybrid information system with images is introduced by means of the inclusion measure between two fuzzy sets. Moreover, a three-way decision method is proposed by using this decision-theoretic rough set model. Finally, to illustrate the feasibility of the proposed method, an application of the proposed method is given by an example of medical diagnosis.