Cancer microarray data feature selection using Multi-Objective Binary Particle Swarm Optimization algorithm

dc.contributor.authorAnnavarapu, Chandra Sekhara Rao
dc.contributor.authorDara, Suresh
dc.contributor.authorBanka, Haider
dc.date.accessioned2016-11-24T15:11:22Z
dc.date.available2016-11-24T15:11:22Z
dc.date.issued2016-08-01
dc.description.abstractCancer investigations in microarray data play a major role in cancer analysis and the treatment. Cancer microarray data consists of complex gene expressed patterns of cancer. In this article, a Multi-Objective Binary Particle Swarm Optimization (MOBPSO) algorithm is proposed for analyzing cancer gene expression data. Due to its high dimensionality, a fast heuristic based pre-processing technique is employed to reduce some of the crude domain features from the initial feature set. Since these pre-processed and reduced features are still high dimensional, the proposed MOBPSO algorithm is used for finding further feature subsets. The objective functions are suitably modeled by optimizing two conflicting objectives i.e., cardinality of feature subsets and distinctive capability of those selected subsets. As these two objective functions are conflicting in nature, they are more suitable for multi-objective modeling. The experiments are carried out on benchmark gene expression datasets, i.e., Colon, Lymphoma and Leukaemia available in literature. The performance of the selected feature subsets with their classification accuracy and validated using 10 fold cross validation techniques. A detailed comparative study is also made to show the betterment or competitiveness of the proposed algorithm.en
dc.identifier.doi10.17179/excli2016-481
dc.identifier.issn1611-2156
dc.identifier.urihttp://hdl.handle.net/2003/35620
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-17661
dc.language.isoen
dc.relation.ispartofseriesEXCLI Journal;Vol. 15, 2016
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectcancer micro arrayen
dc.subjectgene expressionsen
dc.subjectfeature selectionen
dc.subjectbinary PSOen
dc.subjectclassificationen
dc.subject.ddc610
dc.titleCancer microarray data feature selection using Multi-Objective Binary Particle Swarm Optimization algorithmen
dc.typeText
dc.type.publicationtypearticle
dcterms.accessRightsopen access
eldorado.dnb.zdberstkatid2132560-1

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