Selecting informative genes by lasso and dantzig selector for linear classifiers
Automatically selecting a subset of genes with strong discriminative power is a very important step in classification problems based on gene expression data. Lasso and Dantzig selector are known to have automatic variable selection ability in linear regression analysis. This paper employs Lasso and Dantzig selector to select most informative genes for representing the class label as a linear function of gene expression data. The selected genes are further used to fit linear classifiers for cancer classification. On 3 publicly available cancer datasets, the experimental results show that in general, Lasso is more capable than Dantzig selector in selecting informative genes for classification.
Cancer classification, Dantzig selector, Gene selection, Lasso
Zheng, Songfeng, and Weixiang Liu. "Selecting informative genes by lasso and dantzig selector for linear classifiers." In 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 677-680. IEEE, 2010.
Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010