Penalized logistic regression with the adaptive LASSO for gene selection in high-dimensional cancer classification.
Zakariya Yahya AlgamalMuhammad Hisyam LeePublished in: Expert Syst. Appl. (2015)
Keyphrases
- logistic regression
- gene selection
- cancer classification
- generalized linear models
- microarray data
- high dimensional
- gene expression data
- variable selection
- loss function
- microarray
- feature selection
- chi square
- cancer diagnosis
- decision trees
- support vector
- random forest
- gene expression
- gene expression profiles
- naive bayes
- dna microarray
- colon cancer
- breast cancer
- informative genes
- microarray datasets
- high dimensionality
- feature space
- high dimensional data
- model selection
- fold cross validation
- feature ranking
- support vector machine svm
- data mining
- microarray analysis
- training set
- support vector machine
- neural network
- machine learning
- gene sets
- image classification
- data sets