A Classification System Based on Fuzzy Class Association Rules

In order to build a high performance classification system, fuzzy sets are applied to soften the partition boundary of quantitative attributes, and an algorithm for mining fuzzy class association rules is proposed Because fuzzy sets are much closer to human thinking, fuzzy class association rules mined are easily understandable to human Then a classification system based on fuzzy class association rules is proposed, and a genetic algorithm is used to train the classification system Finally some results of instance analysis are given to prove that the classification system has good accuracy and interpretability