Semi-supervized feature reduction for bio-data analysis
73 p.
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2011
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| Online Access: | http://hdl.handle.net/10356/46749 |
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sg-ntu-dr.10356-467492023-07-04T15:28:26Z Semi-supervized feature reduction for bio-data analysis Liu, Yun. Chen Lihui School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies 73 p. Cancer classification is one of the most important applications in microarray data analy-sis. Due to high dimensional natures of the microarray data, feature reduction has drawn special attention. In this project, we target to explore effective and semi-supervised fea-ture reduction methods for the gene expression data classification. Two new feature re-duction methods have been explored, analyzed and tested on several microarray datasets. One is a semi-supervised feature selection method and the other one is semi-supervised feature extraction method via label propagation. Master of Science (Signal Processing) 2011-12-23T07:43:24Z 2011-12-23T07:43:24Z 2010 2010 Thesis http://hdl.handle.net/10356/46749 Nanyang Technological University application/pdf |
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Singapore Singapore |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies Liu, Yun. Semi-supervized feature reduction for bio-data analysis |
| description |
73 p. |
| author2 |
Chen Lihui |
| author_facet |
Chen Lihui Liu, Yun. |
| format |
Theses and Dissertations |
| author |
Liu, Yun. |
| author_sort |
Liu, Yun. |
| title |
Semi-supervized feature reduction for bio-data analysis |
| title_short |
Semi-supervized feature reduction for bio-data analysis |
| title_full |
Semi-supervized feature reduction for bio-data analysis |
| title_fullStr |
Semi-supervized feature reduction for bio-data analysis |
| title_full_unstemmed |
Semi-supervized feature reduction for bio-data analysis |
| title_sort |
semi-supervized feature reduction for bio-data analysis |
| publishDate |
2011 |
| url |
http://hdl.handle.net/10356/46749 |
| _version_ |
1772826006705405952 |