A comparative study of classification methods for microarray data analysis
Paper
Paper/Presentation Title | A comparative study of classification methods for microarray data analysis |
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Presentation Type | Paper |
Authors | Hu, Hong (Author), Li, Jiuyong (Author), Plank, Ashley (Author), Wang, Hua (Author) and Daggard, Grant (Author) |
Editors | Christen, Peter, Kennedy, Paul J., Li, Jiuyong, Simoff, Simeon J. and Williams, Graham J. |
Journal or Proceedings Title | Proceedings of the 5th Australasian Data Mining Conference (AusDM 2006): Data Mining and Analytics 2006 |
Number of Pages | 5 |
Year | 2006 |
Place of Publication | Canberra, Australia |
ISBN | 1920682422 |
Web Address (URL) of Paper | http://www.crpit.com/confpapers/CRPITV61Hu.pdf |
Conference/Event | 5th Australasian Conference on Data Mining and Analystics (AusDM 2006) |
Event Details | 5th Australasian Conference on Data Mining and Analystics (AusDM 2006) Parent Australasian Data Mining Conference (AusDM) Event Date 29 to end of 30 Nov 2006 Event Location Sydney, Australia |
Abstract | In response to the rapid development of DNA Microarray technology, many classification methods have been used for Microarray classification. SVMs, decision trees, Bagging, Boosting and Random Forest are commonly used methods. In this paper, we conduct experimental comparison of LibSVMs, C4.5, BaggingC4.5, AdaBoostingC4.5, and Random Forest on seven Microarray cancer data sets. The experimental results show that all ensemble methods outperform C4.5. The experimental results also show that all five methods benefit from data preprocessing, including gene selection and discretization, in classification accuracy. In addition to comparing the average accuracies of ten-fold cross validation tests on seven data sets, we use two statistical tests to validate findings. We observe that Wilcoxon signed rank test is better than sign test for such purpose. |
Keywords | microarray data, classification |
ANZSRC Field of Research 2020 | 490501. Applied statistics |
469999. Other information and computing sciences not elsewhere classified | |
310505. Gene expression (incl. microarray and other genome-wide approaches) | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Department of Mathematics and Computing |
Department of Biological and Physical Sciences |
https://research.usq.edu.au/item/9y0xw/a-comparative-study-of-classification-methods-for-microarray-data-analysis
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