Joint covariate selection and joint subspace selection for multiple classification problems
Joint covariate selection and joint subspace selection for multiple classification problems
We address the problem of recovering a common set of covariates that are relevant simultaneously to several classification problems. By penalizing the sum of ℓ 2 norms of the blocks of coefficients associated with each covariate across different classification problems, similar sparsity patterns in all models are encouraged. To take …