OHPL
Ordered Homogeneity Pursuit Lasso for Group Variable Selection
v1.4.1
·
Jul 20, 2024
·
GPL-3 | file LICENSE
Description
Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) <DOI:10.1016/j.chemolab.2017.07.004>. The OHPL method exploits the homogeneity structure in high-dimensional data and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spectroscopic data.
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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
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1.4.1
Mar 9, 2026