Sparse regression for related problems
Arguments
- x
n x p matrix (multi-task learning) or list of n_k x p matrices (transfer learning)
- y
n x q matrix (multi-task learning) or list of n_k-dimensional vectors (transfer learning)
- family
character "gaussian" or "binomial"
- alpha.init
elastic net mixing parameter for initial regressions, default: 0.95 (lasso-like elastic net)
- alpha
elastic net mixing parameter of final regressions, default: 1 (lasso)
- type
character
- nfolds
number of cross-validation folds