• Home
• Library
• DRO home

A Hybrid PSO-FSVM Model and Its Application to Imbalanced Classification of Mammograms Samma, Hussein, Lim, Chee Peng and Ngah, Umi Kalthum 2013, A Hybrid PSO-FSVM Model and Its Application to Imbalanced Classification of Mammograms, in Intelligent information and database systems: 5th Asian conference, ACIIDS 2013, Kuala Lumpur, Malaysia, March 18-20, 2013, proceedings : Part 1, Springer, Berlin, Germany, pp.275-284. Attached Files Name Description MIMEType Size Downloads Title A Hybrid PSO-FSVM Model and Its Application to Imbalanced Classification of Mammograms Author(s) Samma, Hussein Lim, Chee Peng Ngah, Umi Kalthum Title of book Intelligent information and database systems: 5th Asian conference, ACIIDS 2013, Kuala Lumpur, Malaysia, March 18-20, 2013, proceedings : Part 1 Editor(s) Selamat, Ali Nguyen, Ngoc Thanh Haron, Habibollah Publication date 2013 Chapter number 29 Total chapters 52 Start page 275 End page 284 Total pages 10 Publisher Springer Place of Publication Berlin, Germany Summary In this work, a hybrid model comprising Particle Swarm Optimization (PSO) and the Fuzzy Support Vector Machine (FSVM) for tackling imbalanced classification problems is proposed. A PSO algorithm, guided by the G-mean measure, is used to optimize the FSVM parameters in imbalanced classification problems. The hybrid PSO-FSVM model is evaluated using a mammogram mass classification problem. The experimental results are analyzed and compared with those from other methods. The outcomes positively demonstrate that the proposed PSO-FSVM model is able to achieve comparable, if not better, results for imbalanced data classification problems. ISBN 9783642365454 9783642365461 Language eng Field of Research 080108 Neural, Evolutionary and Fuzzy Computation Socio Economic Objective 920203 Diagnostic Methods HERDC Research category B1 Book chapter Copyright notice ©2013, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30057218 Document type: Book Chapter Collection: Centre for Intelligent Systems Research Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 23 Oct 2013, 11:12:22 EST Mon, 23 Dec 2013, 09:12:48 EST Mon, 23 Dec 2013, 09:21:30 EST Mon, 23 Dec 2013, 09:29:07 EST Thu, 09 Jan 2014, 08:58:44 EST Thu, 16 Jan 2014, 13:19:27 EST Thu, 13 Mar 2014, 16:36:11 EST Fri, 14 Mar 2014, 07:39:01 EST Tue, 18 Mar 2014, 10:30:55 EST Tue, 18 Mar 2014, 15:11:56 EST Tue, 18 Mar 2014, 15:13:12 EST Wed, 19 Mar 2014, 14:51:28 EST Filtered Full Access Statistics: 27 Abstract Views, 9 File Downloads  -  Detailed Statistics Created: Wed, 23 Oct 2013, 11:12:22 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.