Interval improved fuzzy partitions fuzzy C-means under Hausdorff distance
S.-C. Chang, W.-C. Chuang, Jin-Tsong Jeng · IET conference proceedings. · 2024
Symbolic interval data analysis (SIDA) has been successfully applied in a wide range of fields, making it a valuable tool for many researchers for the incorporation of uncertainty and imprecision in data, which is often present in real -world scenarios. This paper proposed the interval improved fuzzy partitions fuzzy C-means (IIFPFCM) clustering algorithm that independently combined with Hausdorff distance from the viewpoint of fast convergence and dealing with SIDA with outliers than the traditional interval fuzzy c-means. From the experimental results, IIFPFCM with Hausdorff distance can effectively improve the convergence speed and process the data of outliers.