Mining minimal discriminatice features sets and its applications to gene expression data analysis
Feature subset selection has been an important problem in machine learning research. Recently, new appeared data with high dimensionality, such as microarray gene expression data and text classification data, drive feature subset selection techniques advance speedily.
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2010
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| Online Access: | https://hdl.handle.net/10356/40532 |
| _version_ | 1826118411634081792 |
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| author | Feng, Chu |
| author2 | Wang Lipo |
| author_facet | Wang Lipo Feng, Chu |
| author_sort | Feng, Chu |
| collection | NTU |
| description | Feature subset selection has been an important problem in machine learning research. Recently, new appeared data with high dimensionality, such as microarray gene expression data and text classification data, drive feature subset selection techniques advance speedily. |
| first_indexed | 2024-10-01T04:43:17Z |
| format | Thesis |
| id | ntu-10356/40532 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:43:17Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | ntu-10356/405322023-07-04T16:53:03Z Mining minimal discriminatice features sets and its applications to gene expression data analysis Feng, Chu Wang Lipo School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Feature subset selection has been an important problem in machine learning research. Recently, new appeared data with high dimensionality, such as microarray gene expression data and text classification data, drive feature subset selection techniques advance speedily. DOCTOR OF PHILOSOPHY (EEE) 2010-06-16T04:52:25Z 2010-06-16T04:52:25Z 2008 2008 Thesis Feng, C. (2008). Mining minimal discriminatice features sets and its applications to gene expression data analysis. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/40532 10.32657/10356/40532 en 170 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Feng, Chu Mining minimal discriminatice features sets and its applications to gene expression data analysis |
| title | Mining minimal discriminatice features sets and its applications to gene expression data analysis |
| title_full | Mining minimal discriminatice features sets and its applications to gene expression data analysis |
| title_fullStr | Mining minimal discriminatice features sets and its applications to gene expression data analysis |
| title_full_unstemmed | Mining minimal discriminatice features sets and its applications to gene expression data analysis |
| title_short | Mining minimal discriminatice features sets and its applications to gene expression data analysis |
| title_sort | mining minimal discriminatice features sets and its applications to gene expression data analysis |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems |
| url | https://hdl.handle.net/10356/40532 |
| work_keys_str_mv | AT fengchu miningminimaldiscriminaticefeaturessetsanditsapplicationstogeneexpressiondataanalysis |