Variable Selection in a Log-Linear Birnbaum-Saunders Regression Model for High-Dimensional Survival Data via the Elastic-Net and Stochastic EM.
Yu-kun ZhangXuewen LuAnthony F. DesmondPublished in: Technometrics (2016)
Keyphrases
- variable selection
- regression model
- elastic net
- survival analysis
- high dimensional
- survival data
- model selection
- cross validation
- input variables
- mixture model
- expectation maximization
- high dimensional data
- gaussian process
- low dimensional
- unsupervised learning
- dimension reduction
- linear model
- em algorithm
- dimensionality reduction
- feature selection
- parameter estimation
- data points
- k means
- high dimensionality
- multiple kernel learning
- ls svm
- input space
- sample size
- nearest neighbor
- feature space
- generative model
- maximum likelihood
- bayesian framework
- hyperparameters
- data sets
- decision trees
- least squares
- image processing
- machine learning