Name
Title | ||
|---|---|---|
Biomarker discovery using 1-norm regularization for multiclass earthworm microarray gene expression data |
Abstract | ||
|---|---|---|
Novel biomarkers can be discovered through mining high dimensional microarray datasets using machine learning techniques. Here we propose a novel recursive gene selection method which can handle the multiclass setting effectively and efficiently. The selection is performed iteratively. In each iteration, a linear multiclass classifier is trained using 1-norm regularization, which leads to sparse weight vectors, i.e., many feature weights are exactly zero. Those zero-weight features are eliminated in the next iteration. The empirical results demonstrate that the selected features (genes) have very competitive discriminative power. In addition, the selection process has fast rate of convergence. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.neucom.2011.09.035 | Neurocomputing |
Keywords | DocType | Volume |
1-norm regularization,empirical result,next iteration,fast rate,selection process,biomarker discovery,novel biomarkers,expression data,novel recursive gene selection,multiclass earthworm microarray gene,feature weight,competitive discriminative power,linear multiclass classifier,multiclass classification | Journal | 92, |
ISSN | Citations | PageRank |
0925-2312 | 4 | 0.47 |
References | Authors | |
14 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaofei Nan | 1 | 134 | 7.18 |
| Nan Wang | 2 | 14 | 0.94 |
| Ping Gong | 3 | 46 | 2.30 |
| Chaoyang Zhang | 4 | 230 | 22.23 |
| Yixin Chen | 5 | 34 | 2.23 |
| Dawn , Wilkins | 6 | 415 | 27.30 |