Null Space LDA Based Feature Extraction of Mass Spectrometry Data for Cancer Classification.
Lei ZhuBin HanLihua LiShenhua XuHangzhou MouZhiguo ZhengPublished in: BMEI (2009)
Keyphrases
- mass spectrometry data
- null space
- cancer classification
- linear discriminant analysis
- feature extraction
- feature selection
- gene selection
- pattern classification
- discriminant analysis
- random forest
- microarray
- gene expression data
- microarray data
- support vector machine svm
- small sample size
- face recognition
- dimension reduction
- principal component analysis
- dimensionality reduction
- gene expression profiles
- principal components
- feature set
- high throughput
- feature vectors
- gene expression
- feature space
- high dimensional data
- pattern recognition
- support vector
- image processing
- experimental conditions
- machine learning
- image classification
- classification accuracy
- chi square
- computer vision
- learning algorithm
- high dimensionality
- support vector machine
- gene ontology
- gene sets