PROBABILISTIC SETS AND FUZZY-REASONING FOR DATA-ANALYSIS PROBLEMS

This paper presents two methods based on probabilistic sets to achieve some problems in data analysis. We are indebted to Professor Arnold K aufmann for the beginnings of these two methods; some of the first ide as were found in his profile work. The first method is related to subj ective data analysis, the second one is an approach for establishing a relationship two data sets, the first one having a subjective origin and the second one being objective. The purpose of this paper is not t o compete with improved data analysis methods but to propose, if data can be taken into account as probabilistic fuzzy sets, to use such a r epresentation, which loses very little information. Both methods were tested on real data and the results compared with those obtained with improved data analysis methods, mainly those of the Principal Componen t Analysis and Multiple Correspondence Factor Analysis.