Name
Abstract | ||
|---|---|---|
Microarray datasets comprise a large number of gene expression values and a relatively small number of samples. Feature selection algorithms are very useful in these situations in order to find a compact subset of informative features. We propose a redundancy control method for algorithms in the recently proposed SPEC family of spectral-based feature selection algorithms. This method is applied to find relevant genes in order to cluster samples corresponding to three kinds of cancer: lung, breast and colon. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICMLA.2009.86 | ICMLA |
Keywords | Field | DocType |
spectral-based feature selection algorithm,microarray datasets,redundancy control method,cluster sample,spectral clustering,small number,microarray data,feature selection,feature selection algorithm,large number,informative feature,spec family,compact subset,gene expression,cluster sampling,redundancy,feature extraction,data mining,mutual information,colon cancer,genetics,bioinformatics,cancer,breast cancer,clustering algorithms | Data mining,Spectral clustering,Feature selection,Pattern recognition,Computer science,Feature extraction,Redundancy (engineering),Minimum redundancy feature selection,Microarray analysis techniques,Artificial intelligence,Mutual information,Cluster analysis | Conference |
ISBN | Citations | PageRank |
978-0-7695-3926-3 | 2 | 0.44 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Darío García-García | 1 | 24 | 4.41 |
| Raúl Santos-Rodríguez | 2 | 36 | 12.41 |
| Santos-Rodriguez, R. | 3 | 2 | 0.44 |