Semi-supervised SVM-based feature selection for cancer classification using microarray gene expression data

• Main Authors: Ang, Jun Chin, Haron, Habibollah, Abdull Hamed, Haza Nuzly
• Format: Conference or Workshop Item
• Published: 2015
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/59470/; http://dx.doi.org/10.1007/978-3-319-19066-2_45
• Institution: Universiti Teknologi Malaysia

Gene expression data always suffer from the high dimensionality issue, therefore feature selection becomes a fundamental tool in the analysis of cancer classification. Basically, the data can be collected easily without providing the label information, which is quite useful in improving the accuracy...