Ranked-sparsity and hybrid LASSO principal components regression improve fMRI task classification over standard LASSO PCR in several tasks, with gains in cross-validated deviance of up to 51.7%.
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Identifying Neural Signatures from fMRI using Hybrid Principal Components Regression
Ranked-sparsity and hybrid LASSO principal components regression improve fMRI task classification over standard LASSO PCR in several tasks, with gains in cross-validated deviance of up to 51.7%.