dc.contributor.authorZhou, Ninaen_US
dc.date.accessioned2011-12-23T10:01:57Z
dc.date.accessioned2017-07-23T08:33:47Z
dc.date.available2011-12-23T10:01:57Z
dc.date.available2017-07-23T08:33:47Z
dc.date.copyright2009
dc.date.issued2009
dc.identifier.citationZhou, N. (2009). Classification and feature selection for biomedical and biological data using soft computing. Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/46861
dc.description159 p.en_US
dc.description.abstractThis dissertation mainly discusses feature selection and classification problems in the context of bio-medical data. Feature selection and classification are two important tasks in processing bio-medical data. For example, in disease diagnosis, finding the sub-groups of genes or symptoms that are specific to a particular disease is a feature selection problem. Once these sub-groups of genes or symptoms are found, diagnosing the disease which is a classification problem, will become easy. However, because most of the bio-medical data has large numbers of features, feature selection and classification are hence particularly challenging.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systemsen_US
dc.titleClassification and feature selection for biomedical and biological data using soft computingen_US
dc.typeThesisen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.supervisorWang Lipoen_US
dc.description.degreeDOCTOR OF PHILOSOPHY (EEE)en_US


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