Name
Title | ||
|---|---|---|
An efficient gene selection technique based on Self-organizing Map and Particle Swarm Optimization. |
Abstract | ||
|---|---|---|
Among the large amount of genes presented in microarray gene expression data, only a small fraction of them is effective for performing a certain diagnostic test. It is for this reason that reducing the dimensionality of gene expression data is imperative. An improved Self-organizing map method based on neighborhood mutual information correlation measure is proposed, and then combines with Particle swarm optimization method to construct an efficient gene selection algorithm, denoted by ICMSOM-PSO. Experimental results show that the proposed method can reduce the dimensionality of the dataset, and confirm the most informative gene subset and improve classification accuracy. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3233/JIFS-161887 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | Field | DocType |
Self-organizing map,neighborhood mutual information,particle swarm optimization,gene selection | Particle swarm optimization,Gene selection,Multi-swarm optimization,Self-organizing map,Artificial intelligence,Mathematics,Machine learning,Metaheuristic | Journal |
Volume | Issue | ISSN |
33 | 6 | 1064-1246 |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sen Feng | 1 | 17 | 4.32 |
| Jiucheng Xu | 2 | 223 | 20.09 |
| Tianhe Xu | 3 | 18 | 9.82 |