Rule Extraction For Blood Donators With Fuzzy Sequential Pattern Mining

Abstract

Abstract Sequential pattern mining is to discover all sub-sequences that are frequent. The classical sequential pattern mining algorithms do not allow processing of numerical data and require converting these data into a binary representation, which necessarily leads to a loss of information. Fuzzy sets are used to overcome this problem and fuzzy set based algorithms have been proposed to handle numerical data using intervals, particularly fuzzy intervals. In this paper, a fuzzy sequential pattern mining algorithm is applied to mine fuzzy sequential patterns from the Blood Transfusion Service Center data set. It helps to predict future patterns of blood donating behavior.