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pro vyhledávání: '"Juan Carlos Laria"'
Publikováno v:
Mathematics, Vol 10, Iss 16, p 3001 (2022)
The elastic net is among the most widely used types of regularization algorithms, commonly associated with the problem of supervised generalized linear model estimation via penalized maximum likelihood. Its attractive properties, originated from a co
Externí odkaz:
https://doaj.org/article/beff5e3a7245457fa398fa29d60d8713
Publikováno v:
Mathematics; Volume 10; Issue 16; Pages: 3001
Carlos Laria, J, Clemmensen, L H, Ersbøll, B K & Delgado-Gomez, D 2022, ' A Generalized Linear Joint Trained Framework for Semi-Supervised Learning of Sparse Features ', Mathematics, vol. 10, no. 16, 3001 . https://doi.org/10.3390/math10163001
Carlos Laria, J, Clemmensen, L H, Ersbøll, B K & Delgado-Gomez, D 2022, ' A Generalized Linear Joint Trained Framework for Semi-Supervised Learning of Sparse Features ', Mathematics, vol. 10, no. 16, 3001 . https://doi.org/10.3390/math10163001
This article belongs to the Special Issue Applied and Methodological Data Science. The elastic net is among the most widely used types of regularization algorithms, commonly associated with the problem of supervised generalized linear model estimatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::497cb7b6a9ba2db09d38c1c6e9966cf7
Autor:
Laria, Juan Carlos1 (AUTHOR) juank.laria@gmail.com, Clemmensen, Line H.2 (AUTHOR), Ersbøll, Bjarne K.2 (AUTHOR), Delgado-Gómez, David1 (AUTHOR)
Publikováno v:
Mathematics (2227-7390). Aug2022, Vol. 10 Issue 16, p3001-3001. 18p.
Publikováno v:
Gaceta de la Real Sociedad Matematica Espanola; 2021, Vol. 24 Issue 1, p13-24, 12p