Feature dimension reduction for microarray data analysis
Date of Issue2005
School of Electrical and Electronic Engineering
In this project, we target to find effective and unsupervised feature reduction tools for gene expression data classification purpose. We have tackled the problem from both feature selection and feature extraction approaches. Three feature reduction algo- rithms, fast entropy ranking, revised locally linear embedding, and feature grouping are proposed, analyzed and tested on several microarray datasets.
DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits
Nanyang Technological University