Title :
Auto Determining Parameters in Class-Association Mining
Author :
Phan-Luong, Viet
Author_Institution :
LIF, Univ. Aix-Marseille, Marseille, France
Abstract :
This work proposes an approach to determine automatically parameters in classification rule mining based on association rules. Such parameters are the thresholds of support and confidence, and the maximal size of rules. The approach is based on statistical data get on the dataset during the mining process. In particular, the thresholds of support and confidence are not fixed, but varied dependently on each other and on the size of rules.
Keywords :
data mining; statistical analysis; association rule; auto determining parameter; class-association mining; classification rule mining; statistical data; Accuracy; Association rules; Buildings; Itemsets; Subspace constraints; Support vector machines; Data mining; association rule; classification; key itemset;
Conference_Titel :
Advanced Information Networking and Applications (AINA), 2012 IEEE 26th International Conference on
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4673-0714-7
DOI :
10.1109/AINA.2012.18
