A new fuzzy associative classification based on axiomatic fuzzy set theory

Classification is one of the most popular data mining techniques applied to many scientific and industrial problems. Recently, fuzzy association rule has been extensively studied in classification. In this paper, a new classification model is proposed, which is based on interpretable fuzzy association rules and automatic generating membership functions. In addition,a modified algorithm for classification is presented. The results on five data sets indicate that the proposed classifier can be regarded as an accurate and effective classification technique. Compared with other classification approaches and fuzzy logics, a relative error rate is lower in our results.