Open AccessPredicting correlated outcomes from molecular data
Author(s) -
Armin Rauschenberger,
Enrico Glaab
Publication year - 2021
Publication title -
bioinformatics
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab576
Subject(s) - computer science , data mining , data science , computational biology , biology
Multivariate (multi-target) regression has the potential to outperform univariate (single-target) regression at predicting correlated outcomes, which frequently occur in biomedical and clinical research. Here we implement multivariate lasso and ridge regression using stacked generalization.
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