Outlier detection scoring measurements based on frequent pattern technique

Said, A.M. and Dominic, D.D. and Samir, B.B. (2013) Outlier detection scoring measurements based on frequent pattern technique. Research Journal of Applied Sciences, Engineering and Technology, 6 (8). pp. 1341-1347. ISSN 20407459

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Outlier detection is one of the main data mining tasks. The outliers in data are more significant and interesting than common ones in a wide variety of application domains, such as fraud detection, intrusion detection, ecosystem disturbances and many others. Recently, a new trend for detecting the outlier by discovering frequent patterns (or frequent item sets) from the data set has been studied. In this study, we present a summarization and comparative study of the available outlier detection scoring measurements which are based on the frequent patterns discovery. The comparisons of the outlier detection scoring measurements are based on the detection effectiveness. The results of the comparison prove that this approach of outlier detection is a promising approach to be utilized in different domain applications. © Maxwell Scientific Organization, 2013.

Item Type: Article
Additional Information: cited By 4
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:52
Last Modified: 09 Nov 2023 15:52
URI: https://khub.utp.edu.my/scholars/id/eprint/3979

Actions (login required)

View Item
View Item