Classifiers for Gene Micro Array Data Analysis

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dc.categoryConference Proceedings
dc.contributor.authorVasantha Kalyani David
dc.date.accessioned2017-03-30T01:04:07Z
dc.date.available2017-03-30T01:04:07Z
dc.date.issued2010
dc.departmentComputer Scienceen_US
dc.description.abstractResearchers aim to develop an automated system for robust and reliable cancer diagnosis based on gene micro array data. There are methods for evaluating and improving techniques for selecting infonnative genes from micro array data. The genes of interest are selected by ranking them using classical statistical techniques. Various statistical classifiers are applied to get the best classification model. By applying this procedure there is always a need fur two systems; a gene selection method and a classifier, and selection of an optimal gene selection algorithm-classifier pair are difficult. To solve this difficulty, from the study it is found that genetic programming act as a classifier as well as gene selection algorithm. [12].en_US
dc.identifier.urihttps://ir.avinuty.ac.in/handle/avu/2363
dc.langEnglishen_US
dc.publisher.nameProceedings of the National Conference on Advanced Computing Technologiesen_US
dc.publisher.typeNationalen_US
dc.titleClassifiers for Gene Micro Array Data Analysisen_US
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