Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/4847
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dc.contributor.authorMa April Maungen_US
dc.date.accessioned2008-09-17T09:59:49Z
dc.date.available2008-09-17T09:59:49Z
dc.date.copyright2005en_US
dc.date.issued2005
dc.identifier.urihttp://hdl.handle.net/10356/4847
dc.description.abstractThe diversity of the application areas of neural network is a recommendation of the strengths and flexibility of neural networks. There are many application areas for neural networks like aerospace, automotive, electronics, entertainment, food industry, insurance, marketing, manufacturing, medical, speech and telecommunications. Among them we only concentrate in medical application areas. We want to test the patients to find out the diseases. So we need to use the neural network and classify with using neural network algorithms. Among many algorithms, we choose the backpropagation and extreme learning machine algorithms to classify the best network architecture. We use the DNA microarray database for simulation. We considered three problems: MLL_Leukemia, Prostate Cancer and Central Nervous System.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies
dc.titleClassification of the microarray data using neural networksen_US
dc.typeThesisen_US
dc.contributor.supervisorSaratchandran, Paramasivanen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
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