DocumentCode
1835020
Title
Auto Determining Parameters in Class-Association Mining
Author
Phan-Luong, Viet
Author_Institution
LIF, Univ. Aix-Marseille, Marseille, France
fYear
2012
fDate
26-29 March 2012
Firstpage
183
Lastpage
190
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Information Networking and Applications (AINA), 2012 IEEE 26th International Conference on
Conference_Location
Fukuoka
ISSN
1550-445X
Print_ISBN
978-1-4673-0714-7
Type
conf
DOI
10.1109/AINA.2012.18
Filename
6184869
Link To Document