Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/46861
Title: Classification and feature selection for biomedical and biological data using soft computing
Authors: Zhou, Nina
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 2009
Source: Zhou, N. (2009). Classification and feature selection for biomedical and biological data using soft computing. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: This 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.
Description: 159 p.
URI: https://hdl.handle.net/10356/46861
DOI: 10.32657/10356/46861
Rights: Nanyang Technological University
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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