A new local distace-based outlier detection approach for fuzzy data by vertex metric

The way of searching For outlier data based on distance is one of the attractive study in data mining during recent two decades, due to the wide range of applications, has been always investigated. But this wide scope has been limited to certain data, while the valuable ability of fuzzy data in analyzing and applying has been proven. Considering the effective performance of LDOF method as a distance based approach in identifying outlier data, the almost this article is to use the famous vortex metric, to provide a universalization of LDOF method for identifying outlier dataset of fuzzy data. Also performance and efficiency of the proposed method has been investigated in simulation.