Name
Abstract | ||
|---|---|---|
We have investigated strategies for enhancing ensemble learning algorithms for DNA microarray data analysis. By using modified versions of AdaBoost, LogitBoost and BagBoosting we have shown that feature non-replacement provides an effective enhancement to the performance of all three algorithms, and overall, BagBoosting with feature non-replacement had the lowest error rates when used on six commonly-used cancer datasets. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/IJCNN.2007.4370995 | Orlando, FL |
Keywords | Field | DocType |
DNA,biology computing,data analysis,learning (artificial intelligence),AdaBoost,BagBoosting,DNA microarray data analysis,LogitBoost,cancer datasets,ensemble learning algorithms,feature nonreplacement | AdaBoost,Dna microarray data,Pattern recognition,Computer science,Microarray analysis techniques,Artificial intelligence,Boosting (machine learning),LogitBoost,Ensemble learning,Machine learning | Conference |
ISSN | ISBN | Citations |
1098-7576 E-ISBN : 978-1-4244-1380-5 | 978-1-4244-1380-5 | 4 |
PageRank | References | Authors |
0.54 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Geoffrey R. Guile | 1 | 8 | 1.68 |
| Wenjia Wang | 2 | 57 | 9.12 |