Classification of serous ovarian tumors based on microarray data using multicategory support vector machines.
Jee Soo ParkSoo Beom ChoiJai Won ChungSung Woo KimDeok Won KimPublished in: EMBC (2014)
Keyphrases
- microarray data
- ovarian cancer
- gene selection
- support vector
- feature selection
- microarray
- cancer classification
- building classification models
- classification accuracy
- cancer detection
- dna microarray data
- microarray data analysis
- gene expression
- gene expression data
- gene expression profiles
- support vector machine
- cancer diagnosis
- small number of samples
- microarray datasets
- early detection
- data sets
- colon cancer
- dna microarray
- svm classifier
- text classification
- informative genes
- pattern recognition
- cluster analysis
- feature ranking
- gene expression analysis
- gene expression microarray data
- high dimensional
- support vector machine svm
- gene sets
- high dimensionality
- cross validation
- kernel function
- biologically meaningful
- microarray analysis
- supervised learning
- decision boundary
- feature extraction
- feature space
- mass spectra
- logistic regression
- binary classifiers
- tissue samples
- feature vectors
- high throughput
- decision trees
- machine learning