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.
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2010
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/40532 |
| Summary: | 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. |
|---|