A GA-Based Classifier for Microarray Data Classification
| Autor: | Rujirawadee Thammasang, Supoj Hengpraprohm, Suvimol Mukviboonchai, Prabhas Chongstitvatana |
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| Rok vydání: | 2010 |
| Předmět: |
Microarray
business.industry Microarray analysis techniques Computer science Data classification Cancer Feature selection Pattern recognition computer.software_genre medicine.disease Cross-validation Statistical classification Gene expression Genetic algorithm medicine Artificial intelligence Data mining business computer Classifier (UML) |
| Zdroj: | 2010 International Conference on Intelligent Computing and Cognitive Informatics. |
| DOI: | 10.1109/icicci.2010.62 |
| Popis: | This work presents an algorithm for generating the GA-based (Genetic Algorithm) classifier for microarray data classification. The microarray dataset comprises of a small number of samples with very high features. In order to construct the GA-based classifier, a number of informative features (genes) are selected. These features are divided into 2 groups (10 features or less in each group). The summation of gene expression values selected by GA in each group is then calculated and compared between groups. If the summation of the first group is greater than the other, it is classified as class 1; otherwise, it is classified as class 2. In the experiment, 3 microarray benchmark datasets for the 2-class problem are used. There are Lymphoma, Leukemia and Colon datasets. 10-Folds cross validation is used to test the performance of the proposed method. The experimental results show that the proposed GA-based classifier yields a good effectiveness in the 2-class microarray data classification comparing with the other methods. |
| Databáze: | OpenAIRE |
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