Title :
An Improved Method of Outlier Detection Based on Frequent Pattern
Author :
Zhang, Weiwei ; Wu, Jianhua ; Yu, Jie
Author_Institution :
Dept. of Comput. Sci., Jinan Univ., Zhuhai, China
Abstract :
Outlier detection is an interesting data mining task, which detects rare events. This paper focuses on the method of outlier detection based on frequent pattern (FP method for short). First we analyze the drawback of this method, and then an improved method (LFP method for short) has been presented. Finally, we evaluate the two methods by using several datasets and the experiment results show that LFP method outperforms FP method.
Keywords :
data mining; LFP method; data mining; frequent pattern; outlier detection; Accuracy; Algorithm design and analysis; Complexity theory; Computer science; Data mining; Helium; Itemsets; association rules; data mining; frequent pattern; outlier detection;
Conference_Titel :
Information Engineering (ICIE), 2010 WASE International Conference on
Conference_Location :
Beidaihe, Hebei
Print_ISBN :
978-1-4244-7506-3
Electronic_ISBN :
978-1-4244-7507-0
DOI :
10.1109/ICIE.2010.97