Clustering Problem with Fuzzy Data: Empirical Study for Financial Distress Firms

Abstract

In many real applications, the data of classification problems cannot be precisely measured. However, in an increasingly complex environment, these variables can be imprecise, qualitative or linguistic. In such a case, fuzzy set theory seems to be the convenient tool to fill this insufficiency. Thus, we proposed a new approach, based on the ranking function, which consists in solving the classification problems via fuzzy linear programming model. This approach has been applied for the financial distress firms. The obtained results are satisfactory in terms of correctly classified rates