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

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 T-cos-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. Published by Elsevier B.V.