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|Title:||Mining minimal discriminatice features sets and its applications to gene expression data analysis||Authors:||Feng, Chu||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems||Issue Date:||2008||Source:||Feng, C. (2008). Mining minimal discriminatice features sets and its applications to gene expression data analysis. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||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.||URI:||https://hdl.handle.net/10356/40532||DOI:||10.32657/10356/40532||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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