A novel support vector sampling technique to improve classification accuracy and to identify key genes of leukaemia and prostate cancers.
Austin H. ChenChing-Heng LinPublished in: Expert Syst. Appl. (2011)
Keyphrases
- support vector
- prostate cancer
- gene expression profiles
- gene selection
- gene expression data
- complex diseases
- gene expression
- microarray data
- cancer diagnosis
- cancer classification
- microarray datasets
- feature selection
- automatic segmentation
- experimental conditions
- generalization ability
- kernel function
- classification accuracy
- prostate segmentation
- high dimensional
- cell lines
- microarray data analysis
- regulatory networks
- gene ontology
- ultrasound images