Lasso penalized model selection criteria for high-dimensional multivariate linear regression analysis.
Shota KatayamaShinpei ImoriPublished in: J. Multivar. Anal. (2014)
Keyphrases
- model selection criteria
- model selection
- variable selection
- high dimensional
- selection criterion
- regression model
- generalized linear models
- cross validation
- feature selection
- parameter estimation
- sample size
- hyperparameters
- low dimensional
- dimensionality reduction
- dimension reduction
- mixture model
- high dimensional data
- selection criteria
- information criterion
- high dimensionality
- machine learning
- marginal likelihood
- leave one out cross validation
- statistical tests
- data points
- least squares
- feature extraction
- nearest neighbor
- feature space
- gaussian process
- parameter space
- ridge regression
- semi supervised
- face recognition