Dimension Reduction-Based Penalized Logistic Regression for Cancer Classification Using Microarray Data.
Li ShenEng Chong TanPublished in: IEEE ACM Trans. Comput. Biol. Bioinform. (2005)
Keyphrases
- dimension reduction
- logistic regression
- cancer classification
- microarray data
- high dimensional
- loss function
- cluster analysis
- feature selection
- gene selection
- variable selection
- microarray
- high dimensionality
- support vector
- gene expression data
- cancer diagnosis
- naive bayes
- low dimensional
- gene expression
- principal component analysis
- decision trees
- maximum likelihood
- least squares
- feature extraction
- gene expression profiles
- chi square
- feature space
- model selection
- breast cancer
- linear discriminant analysis
- data sets
- dimensionality reduction
- high dimensional data
- clustering algorithm
- pairwise
- microarray datasets
- classification accuracy
- fold cross validation
- machine learning
- nearest neighbor
- discriminant analysis
- unsupervised learning
- gene sets
- training samples
- text categorization
- feature set
- data analysis
- computer vision
- learning algorithm
- data mining
- neural network