Innovative feature selection methods for bioinformatics

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...

Full description

Saved in:
Bibliographic Details
Main Author: Yan, Lin
Other Authors: Wang Lipo
Format: Final Year Project
Language:English
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/10356/50246
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary: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.