Boosting for feature selection for microarray data analysis
| Autor: | Geoffrey R. Guile, Wenjia Wang |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Boosting (machine learning)
Artificial neural network business.industry Computer science Microarray analysis techniques Feature extraction Pattern recognition Feature selection Machine learning computer.software_genre complex mixtures Statistical classification ComputingMethodologies_PATTERNRECOGNITION Wilcoxon-Mann-Whitney U Test Artificial intelligence business computer |
| Zdroj: | IJCNN |
| DOI: | 10.1109/ijcnn.2008.4634156 |
| Popis: | We have investigated the use of boosting techniques for feature selection for microarray data analysis. We propose a novel algorithm for feature selection and have tested it on three datasets. The results clearly show that our boosting technique for feature selection outperformed the Wilcoxon-Mann-Whitney U-test commonly used in microarray data analysis, and produced more accurate boosting ensembles when they were constructed with the features selected by our technique. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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