The 11th International Conference on Fuzzy Systems and Data Mining (FSDM 2025)

Abstract: Fuzzy C-Means (FCM) is a clustering algorithm based on partition of the universe. However, the partition generated by an equivalence relation is strict in practical application and exhibits relatively poor fault-tolerant mechanism. In this paper, a novel binary relation based on improved FCM with the principle of refined justifiable granularity is presented. Different expressions of the proposed binary relation under different values of weight parameter are discussed, and the changes of the properties of the binary relation under different parameter values are provided. By measuring the significance of attributes in the feature space, a feature selection method, called forward heuristic feature selection (FHFS), is designed to construct the low-dimension feature space based on maximizing the original data and information retention through the defined degrees of aggregation and dispersion. It is shown how the results of feature selection and classification performance vary when the values of the weight factor locate in different ranges. To illustrate the superiority and effectiveness of the proposed FHFS algorithm, nine high-dimensional datasets and eight image datasets from UCI repository are used and compared with other feature selection methods, respectively. The results of experimental evaluation and the significance test show that the proposed learning mechanism is a superior algorithm.

Biography: Dr. Wentao Li received the Ph.D degree from the Department of Mathematics, Harbin Institute of Technolofy, Harbin, in 2019. From 2016 to 2018, he was a Joint Ph.D Student with the University of Alberta, Edmonton. He is currently with the College of Artificial Intelligence, Southwest University, Chongqing. His current research interests include granular computing modeling and uncertainty measurement theory and applications. In recent years, he has published over 60 articles in international journals such as IEEE TCYB, IEEE TFS, IEEE TNNLS, IEEE TSMC, IEEE TAI, IEEE TCE, FSS, INS, AIRE, IJAR, and many others. Among them, 7 papers have been selected as “ESI Highly Cited Paper”, and 2 papers have been selected as “ESI Hot paper”. He has been the eight project leaders for National Natural Foundation of China, Postdoctoral Science Foundation of China, National Natural Foundation of Chongqing, Chongqing Municipal Education Commission Science and Technology Innovation projects. He served as the Associate Editor of Discover Artificial Intelligence, the Editorial Board of Computers, Materials & Continua, and Data Science and Management.