Name
Abstract | ||
|---|---|---|
Microarray technology has been widely used in biological and medical research to observe a large number of gene expressions. However, such experiments are usually carried out with few replica or instances, which may lead to poor modelling and analysis. This paper suggests an approach to improve classification by using synthetic data. A new algorithm is proposed to estimate synthetic data value and the generated data are labelled by ensemble methods. Experiments with artificial data and real world data demonstrate that the proposed algorithm is able to generate synthetic data on uncertain regions of classifiers to improve effectiveness and efficiency of classification on microarray data sets. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11596448_119 | CIS (1) |
Keywords | Field | DocType |
microarray technology,artificial data,improving classification,real world data,ensemble method,synthetic data value,gene expression,new algorithm,proposed algorithm,synthetic data,microarray data set,microarray data | Replica,Data mining,Expression (mathematics),Computer science,Handwriting recognition,Microarray analysis techniques,Synthetic data,Artificial intelligence,Gene chip analysis,Classifier (linguistics),Ensemble learning,Machine learning | Conference |
Volume | ISSN | ISBN |
3801 | 0302-9743 | 3-540-30818-0 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shun Bian | 1 | 27 | 1.67 |
| Wenjia Wang | 2 | 57 | 9.12 |