Neuro-fuzzy systems for explaining data sets

Abstract

In this paper we describe ITEMS-a system for the estimation, visualization and exploration of travel data of a mobile workforce. One key feature of ITEMS is the interactive exploration of travel data that is visualized on maps. Users can not only see which journeys were late, on-time or early, but they can also request explanations why a journey was possibly late, for example. We have integrated a neuro-fuzzy system based on NEFCLASS into ITEMS. NEFCLASS generates explanatory fuzzy rules for a selected data subset in real time and presents them to the user. The rules can help the user in understanding the data better and in spotting possible problems in workforce management. We discuss aspects of learning interpretable fuzzy rules for generating explanations and demonstrate the application of NEFCLASS in the context of ITEMS.