Rough set approach to approximation of concepts from taxonomy
Sinh Hoa Nguyen, Hung Son Nguyen · 2004
We present a hierarchical learning approach to approximation of complex concept from experimental data using concept taxonomy as a given domain knowledge. The proposition is based on rough set and rough mereology theory. We examine the effectiveness of the proposed approach by comparing it with standard learning approaches with respect to different criteria. Our experiments are performed on benchmark data set as well as on artificial data sets generated by a road traffic simulator.