NDLI: Unsupervised hybrid PSO - Quick reduct approach for feature reduction

Content Provider	IEEE Xplore Digital Library
Author	Inbarani, H.H. Nizar Banu, P.K. Andrews, S.
Copyright Year	2012
Description	Author affiliation: Department of Computer Applications, B. S. Abdur Rahman University, Chennai, India (Nizar Banu, P.K.) \|\| Department of Computer Science, Periyar University, Salem, India (Inbarani, H.H.) \|\| School of Computing Science and Engineering, VIT University, Chennai Campus, India (Andrews, S.)
Abstract	Feature reduction reduces the dimensionality of a database and selects more informative features by removing the irrelevant features. Selecting features in unsupervised learning scenarios is a harder problem than supervised feature selection due to the absence of class labels that would guide the search for relevant features. PSO is an evolutionary computation technique which finds global optimum solution in many applications. Rough set is a powerful tool for data reduction based on dependency between attributes. This work combines the benefits of both PSO and rough sets. This paper describes a novel Unsupervised PSO based Quick Reduct (US-PSO-QR) for feature selection which employs a population of particles existing within a multi-dimensional space. The performance of the proposed algorithm is compared with the existing unsupervised feature selection methods and the efficiency is measured by using K-Means Clustering and Rough K-Means Clustering.
Starting Page	11
Ending Page	16
File Size	291240
Page Count	6
File Format	PDF
ISBN	9781467315999
e-ISBN	9781467316019
DOI	10.1109/ICRTIT.2012.6206775
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-19
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Iris Lungs Clustering algorithms Breast tissue Particle Swarm Optimization (PSO) Quick Reduct Indexes Unsupervised Feature Selection Lenses Cancer
Content Type	Text
Resource Type	Article

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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
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