Selecting the Most Representative Sample is NP-Hard: Need for Expert (Fuzzy) Knowledge

Authors

J. Esteban Gamez
Francois Modave
Olga Kosheleva, The University of Texas at El PasoFollow

Publication Date

3-2008

Comments

Technical Report: UTEP-CS-08-14a

Published in Proceedings of the IEEE World Congress on Computational Intelligence WCCI'2008, Hong Kong, China, June 1-6, 2008, pp. 1069-1074.

Abstract

One of the main applications of fuzzy techniques is to formalize the notions of "typical", "representative", etc.

The main idea behind fuzzy techniques is that they formalize expert knowledge expressed by words from natural language.

In this paper, we show that if we do not use this knowledge, i.e., if we only use the data, then selecting the most representative sample becomes a computationally difficult (NP-hard) problem. Thus, the need to find such samples in reasonable time justifies the use of fuzzy techniques.