Please use this identifier to cite or link to this item:
|Title:||Innovative feature selection methods for bioinformatics||Authors:||Yan, Lin||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics||Issue Date:||2012||Abstract:||Feature selection has become the focus of much research in areas of application for which datasets with hundreds of thousands of variables are available. These areas include statistics, pattern recognition, machine learning, and knowledge discovery, gene expression array analysis, and combinatorial chemistry. With feature selection, we can improve the prediction performance of the predictors, provide faster and more cost-effective predictors, and provide a better understanding of the underlying process that generated data.||URI:||http://hdl.handle.net/10356/50246||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.