Sparse classification with paired covariates
Sparse classification with paired covariates is a scholarly work, published in 2019 in ''Advances in Data Analysis and Classification''. The main subjects of the publication include weighting, data set, mathematics, dependent and independent variables, Genomic selection, Lasso, real-time polymerase chain reaction, regularization, set, statistics, and computer science. The authors tested the paired lasso on more than 2000 classification problems with experimental genomics data, and found that for estimating sparse but predictive models, the paired lasso outperforms the standard and the adaptive lasso.