Name
Abstract | ||
|---|---|---|
Multiclass classification is an important technique to many complex biomedicine problems. Genetic algorithms (GA) are proven to be effective to select features prior to multiclass classification by support vector machines (SVM). However, their use is computation intensive. Based on SOA (Service Oriented Architecture) design principles, this paper proposes a cloud computing framework that exploits the inherent parallelism of GA-SVM classification to speed up the work. The performance evaluations on an mRNA benchmark cancer dataset have shown the effectiveness and efficiency of the framework. With a user-friendly web interface, the framework provides researchers an easy way to investigate the unrevealed secrets in the fast-growing repository of biomedical data. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ASONAM.2012.139 | ASONAM |
Keywords | Field | DocType |
multiclass classification tool,ga-svm classification,mrna benchmark cancer dataset,important technique,complex biomedicine problem,cloud computing architecture,soa,fast-growing repository,pattern classification,cloud computing framework,biomedical data,service oriented architecture,multiclass classification,svm,cancer,support vector machine,service-oriented architecture,genetic algorithm,genetic algorithms,biomedicine,mrna,performance evaluation,user-friendly web interface,medical computing,feature selection,cloud computing,rna,performance evaluations,design principle,support vector machines,bioinformatics,servers,accuracy | Data mining,Computer science,Support vector machine,Server,Artificial intelligence,User interface,Machine learning,Genetic algorithm,Service-oriented architecture,Cloud computing,Cloud computing architecture,Multiclass classification | Conference |
ISBN | Citations | PageRank |
978-1-4673-2497-7 | 4 | 0.56 |
References | Authors | |
14 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chia-ping Shen | 1 | 43 | 6.07 |
| Chia-Hung Liu | 2 | 169 | 9.57 |
| Feng-Sheng Lin | 3 | 13 | 2.03 |
| Han Lin | 4 | 4 | 0.56 |
| Chi-Ying F Huang | 5 | 204 | 12.95 |
| Cheng-yan Kao | 6 | 586 | 61.50 |
| Feipei Lai | 7 | 846 | 81.35 |
| Jeng-Wei Lin | 8 | 35 | 7.52 |