Bayesian variable selection with sparse and correlation priors for high-dimensional data analysis.
Aijun YangXuejun JiangLianjie ShuJinguan LinPublished in: Comput. Stat. (2017)
Keyphrases
- high dimensional data analysis
- variable selection
- high dimensional
- group lasso
- dimension reduction
- sparsity inducing
- cross validation
- linear models
- structured sparsity
- model selection
- high dimensional data
- random projections
- dimensionality reduction
- preprocessing step
- feature selection
- bayesian framework
- posterior distribution
- relevance vector machine
- sparse representation
- low dimensional
- latent variables
- similarity measure
- neural network
- gaussian processes
- linear discriminant analysis
- singular value decomposition
- feature extraction
- preprocessing