Variable selection for high-dimensional genomic data with censored outcomes using group lasso prior.
Kyu Ha LeeSounak ChakrabortyJianguo SunPublished in: Comput. Stat. Data Anal. (2017)
Keyphrases
- variable selection
- group lasso
- genomic data
- high dimensional
- gene expression data
- high throughput
- biological data
- linear models
- cross validation
- dimension reduction
- dimensionality reduction
- model selection
- high dimensional data
- high dimensionality
- low dimensional
- gene expression
- protein protein interactions
- microarray data
- learning algorithm
- image processing
- data sets
- multi label
- genome wide
- machine learning