NDLI: Outlier detection with Possibilistic Exponential Fuzzy Clustering

Content Provider	IEEE Xplore Digital Library
Author	Treerattanapitak, K. Jaruskulchai, C.
Copyright Year	2011
Description	Author affiliation: Department of Computer Science, Kasetsart University, Bangkok, Thailand (Treerattanapitak, K.; Jaruskulchai, C.)
Abstract	Generally, impact of noise and outliers cause cluster analysis to produce low accuracy. Especially in fuzzy clustering where one data is assigned to all clusters. The centroids are influenced by shifting to another position to include those abnormal points. Therefore, traditional fuzzy clustering like Fuzzy C-Means (FCM) produces the different of membership between data and outliers in polynomial which is not enough to differentiate noise and outliers from normal data. By reformulating objective function in Exponential equation, the algorithm does widen the different gap in exponential. However noise and outliers do not removed by clustering process therefore they are forced to belong in one cluster because of general probabilistic constraint that sum of membership degree of a data across all clusters to 1. By integrating the Possibilistic approach, it allows algorithm to detect outliers. In this paper, we propose Possibilistic Exponential Fuzzy Clustering (PXFCM) that is not only minimizing but cease impact of outliers during the clustering process. Additionally, they are detected and removed for further outlier mining. The comprehensive experiments show that PXFCM produces accurate result for outlier detection while clustering quality is retained.
Starting Page	453
Ending Page	457
File Size	294055
Page Count	5
File Format	PDF
ISBN	9781612841809
e-ISBN	9781612841816
DOI	10.1109/FSKD.2011.6019597
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Possibilistics Noise Breast cancer Exponential Helium Data mining Clustering Equations Outlier Presses Clustering algorithms Anomaly Fuzzy
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in