Feature dimension reduction for microarray data analysis
In this project, we target to find effective and unsupervised feature reduction tools for gene expression data classification purpose. We have tackled the problem from both feature selection and feature extraction approaches. Three feature reduction algo- rithms, fast entropy ranking, revised locall...
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| Format: | Theses and Dissertations |
| Published: |
2008
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| Online Access: | https://hdl.handle.net/10356/3241 |
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| Institution: | Nanyang Technological University |
| Summary: | In this project, we target to find effective and unsupervised feature reduction tools for gene expression data classification purpose. We have tackled the problem from both feature selection and feature extraction approaches. Three feature reduction algo- rithms, fast entropy ranking, revised locally linear embedding, and feature grouping are proposed, analyzed and tested on several microarray datasets. |
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