Name
Abstract | ||
|---|---|---|
Selecting functional genes is essential for analyzing microarray data. Among many available feature (gene) selection approaches, the ones on the basis of the large margin nearest neighbor receive more attention due to their low computational costs and high accuracies in analyzing the high-dimensional data. Yet, there still exist some problems that hamper the existing approaches in sifting real tar... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCBB.2017.2712775 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | Field | DocType |
Cost function,Algorithm design and analysis,Gene expression,Data analysis,Probabilistic logic,Logistics | Data mining,Weighting,Computer science,Regularization (mathematics),Artificial intelligence,Probabilistic logic,Large margin nearest neighbor,k-nearest neighbors algorithm,Gene selection,Algorithm design,Weight,Bioinformatics,Machine learning | Journal |
Volume | Issue | ISSN |
15 | 5 | 1545-5963 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuai An | 1 | 0 | 0.68 |
| Jun Wang | 2 | 0 | 1.01 |
| Jinmao Wei | 3 | 23 | 6.46 |