Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine.
Jooyong ShimInsuk SohnSujong KimJae Won LeePaul E. GreenChangha HwangPublished in: Comput. Stat. Data Anal. (2009)
Keyphrases
- cancer classification
- gene selection
- gene expression profiles
- support vector machine
- feature selection
- microarray data
- microarray
- microarray gene expression data
- gene expression data
- gene expression profiling
- cancer diagnosis
- kernel function
- random forest
- gene expression datasets
- support vector
- gene expression
- informative genes
- unsupervised learning
- gene expression analysis
- cluster analysis
- high dimensionality
- dna microarray
- colon cancer
- self organizing maps
- cancer datasets
- k means
- feature space
- multi class
- microarray datasets
- support vector machine svm
- clustering method
- clustering algorithm
- data clustering
- svm classifier
- gene sets
- k nearest neighbor
- fuzzy clustering
- clustering analysis
- gene ontology
- experimental conditions
- data analysis
- classification accuracy
- feature set
- machine learning
- high throughput
- biological data
- text classification
- supervised learning
- semi supervised
- high dimensional
- training data
- learning algorithm