Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data.
Xuegong ZhangXin LuQian ShiXiu-qin XuHon-chiu E. LeungLyndsay N. HarrisJames D. IglehartAlexander MironJun S. LiuWing Hung WongPublished in: BMC Bioinform. (2006)
Keyphrases
- microarray data
- feature selection
- ovarian cancer
- gene selection
- support vector
- support vector machine
- microarray datasets
- support vector machine svm
- microarray classification
- cancer classification
- microarray data analysis
- classification accuracy
- gene expression data
- mass spectrometry
- microarray
- text classification
- small number of samples
- feature ranking
- text categorization
- feature space
- feature set
- feature selection algorithms
- gene expression
- svm classifier
- gene expression data sets
- high dimensionality
- cancer diagnosis
- gene expression profiles
- high throughput
- biologically relevant
- biological data
- data sets
- high dimensional
- feature extraction
- knn
- feature vectors
- fold cross validation
- biologically meaningful
- feature subset
- mass spectra
- molecular biology
- training set
- dimensionality reduction
- training data
- interaction networks
- machine learning
- clustering algorithm
- decision trees
- unsupervised learning
- gene sets
- nearest neighbor
- biological networks