An Adaptive Algorithm for Mining Fuzzy Association Rules
Shang Guang-long · Computer Technology and Development · 2008
Mining association rules is one of the important research problem in data mining,many algorithms have been proposed to find association rules in database with binary attribute and categorical attribute.Introduce an adaptive algorithm for mining fuzzy association rules.It overcomes the drawbacks caused by the traditional discrete interval method.The algorithm adopts an improved calculating measure of itemset.A method for automatic definition for membership function is proposed,which using fuzzy clustering from training example.The experimental results show that the algorithm is effective and can provide important mining results to users.